Keywords: Integrated traffic management
Abstract: Smart Cities are an example of Cyber-Physical Systems whose goals include improvements in transportation, energy distribution, emergency response, and infrastructure maintenance, to name a few. When it comes to mobility, the availability of large amounts of data, ubiquitous wireless connectivity, and the critical need for scalability open the door for new control and optimization methods with the aim of automating all aspects of mobility, from interconnected self-driving vehicles to sharing transportation resources. We address two key questions: can control and optimization methods enable this automation and, if so, how can we quantify its benets to justify the challenging technological, economic, and social transitions involved? An optimal control framework is presented to show how Connected Automated Vehicles (CAVs) can operate in a dynamic resource contention environment, primarily urban intersections without any trac lights. We also describe how large amounts of actual trac data can be harnessed and drive inverse optimization methods to quantify the value of CAVs in terms of eliminating the prevailing Price of Anarchy: the gap between current "selfish" user-centric and optimal "social" system-centric traffaic equilibria which are achievable with automated mobility.

Keywords: Security, Enterprise Networks, Control and Automation Systems failure
Abstract: Nowadays, the threats on industrial Cyber Physical Systems (CPS) become a major issue. The Industrial Automation Control System (IACS) are a critical and vulnerable part of industries. They interact with the physical world in two ways: by implementing enormous energies at signicant rhythms through their Actuators (A), and by measuring and discretizing at even higher rates the physical values through their Sensors (S). This involves real-time control/command and proscribes latency. In addition, IACS are increasingly controlled by cyberspace through corporate networks and the Internet, that type of system is industrial CPS. These allow the control of the industrial process, the acquisition or the updating of critical parameters, with resources previously reserved for information technology (computer, servers, applications, cloud). Also, the CPS establish a link between low-level networks, eld-bus and high-level computer networks (logistics, commercial, etc.) through several levels of abstraction. This makes it impossible the concrete observation of the system in its environment. In this article, we present our methodology and some results to secure the IACS and its environment. The use of a gateway on eld-bus between S/A and the programmable logic controller allows detection and reaction to threat.

Keywords: Intelligent Transportation, Innovation (in development contexts)
Abstract: Abstract: The autonomous vehicle is meant to drive by itself without any driver intervention. The Autonomous Driving (AD) function is based on the Electric/Electronic architecture of the vehicle constituted of sensors, actuators, ECUs (Electronic Control Unit) and communication networks. The focus of this study is on the different states of the AD function, implemented in different ECUs. Traditionally the system design process distinguishes between the systems engineering process and the safety process. In this application, the first process specifies the functional requirements for the AD function while, in the second one, three redundant sub-functions are considered to ensure a continuous service under failure. Each of the two processes might have its own constraints and planning. So, the safety requirements might come often too late to be taken into account in the systems engineering process without major impacts on the design of the vehicle. More than other functions, with respect to its complexity, the AD function imposes to consider the safety requirements at the beginning of the systems engineering process. To achieve this, a state model of the AD function has been built. It allows integrating functional and redundancy aspects, formalizing the approach and formally verifying requirements of interest. The built model will ensure the consistency between the two design processes, functional and safety. Keywords: Autonomous vehicle, safety analysis, systems engineering, requirements analysis, design systems, discrete-event dynamic systems, redundancy control

Keywords: Connected Vehicles, Low cost technologies
Abstract: Keywords: Tracking Systems, SATCOM On The Move, Least Squares Estimator, Inertially Stabilized Platform, Antennas, Identification.

The only way to insure a good satellite communication data rate on a moving vehicle is to maintain an antenna bore-sight in the satellite direction. To do so, the antenna is mounted on an Antenna Positioning Systems(APS). The APS is a motorized gimbals that make the antenna move in order to maintain a proper pointing, regardless the vehicle movements. This kind of satellite communication is called SATCOM On The Move (SOTM). In this paper, an hybrid pointing strategy, using least squares identification and gyroscopes is proposed and tested through realistic simulation. The main difference with other strategies is that the scanning is made using only the motion due to measurement noise and gyroscope drift, making unnecessary the introduction of a pointing dither on purpose, as it is usually done. Such a dither is referred as self-induced dither. The main advantage of this strategy is its robustness with respect to non-linearities due to mechanical faults since no precise dither trajectory has to be followed. Another benefit is that attitude measurements are not used during tracking, making the strategy proposed especially interesting for low cost applications.

Keywords: Data-Driven Decision Making
Abstract: The monitoring of mechanical systems aims at detecting and diagnosing damages, in general by using output-only vibration measurements under ambient excitation. In this paper, a method is proposed for the localization of stiffness changes in a structure. Based on mechanical grounds, damage is located in elements of a structure with zero stress when a load is applied that is in the null space of the transfer matrix difference between the nominal reference and the damaged state. This load vector is estimated from system identification in both reference and damaged states, and the stress is computed based on a finite element (FE) model of the structure in the reference state. In this work, we address two sources of errors in this computation that lead to stress that is only approximately zero in the damaged elements, which are (1) estimation errors due to noise and finite data, and (2) modal truncation errors due to a limited number of identified modes in comparison to the number of modes present in the FE model that characterizes the structural behavior. To address (1), we propose a statistical evaluation of the stress estimates for a decision on the damaged elements, by propagating the covariance from system identification results to the covariance of the stress. To address (2), several stress estimates are obtained for different mode sets and Laplace variables in the evaluation of the transfer matrices, and jointly evaluated in a hypothesis test. Damage localization results are presented in a simulation study and on experimental data from a damaged beam in the lab.

Keywords: Intrastructure (including energy, telecoms, political, physical etc.), Econometric methods
Abstract: The exponential growth of internet traffic over the last twenty years presents a real challenge to ISP looking to ensure a reliable and efficient service to their customers. Network traffic is far from being straightforward to predict and a deep understanding of the routing domains is a first requirement to achieve proper management of the traffic.

This paper focuses on the monitoring and characterisation of traffic for a European Tier-2 operator (Post Luxembourg). It aims, at first, to provide a thorough analysis of the traffic passing through the network using a Netflow collection process. Secondly, it provides a first approach to model the AS-level traffic using a time-series analysis approach.

Keywords: Service Engineering Applications, Complexity modelling, Systems Theory
Abstract: Product-Service System (PSS) has been proposed as a new value-creation strategy to handle the economic, social, technological and environmental challenges. Despite the numerous proposed methodologies, PSS development is still indeterminate. In order to solve this issue, either product or service development processes are adopted. Though, a customized development process according to PSS characteristics as an integrated system seems more efficient. In this context, Systems Engineering (SE) could be advantageous since it supports a wide range of activities through systems lifecycle. Secondly, it supports integrating the interconnected heterogeneous components of the PSS. This paper aims to explore the idea of extending the use of Model-Based Systems Engineering (MBSE) to PSS to integrate different viewpoints in PSS lifecycle and development process.

Keywords: Systems Theory, Project Management
Abstract: Currently, the relationships among different actors in the project are shaped by many new challenges such as multiplication of data and information, mass customization, global cooperation, scarcity of resources, etc. When managers have several projects to be scheduled, human resources allocation becomes much more complex to grasp. In order to cope with adaption of Product-Process-Organization (P-P-O) model for industry of the future, it is also necessary to have a methodology to approach the problem of human resources allocation.

Keywords: Supply Logistics, Intelligent Transportation
Abstract: In order to collect whole blood from donors and distribute labile blood products to receivers, the French Blood Establishment (EFS) has to deal with several steps of transportation. Knowing the lifetime of each product, their storage conditions, their sensitiveness, and how vital they are for dozens of patients, we demonstrate why it is so important to improve the transportation processes. Currently, these steps are not agile neither efficient. The main reason is that traceability is performed for each transport container but it is time consuming and all the data are not gathered in real time. In order to improve the tracking and monitoring of this activity with reliable data, we suggest using both a Physical Internet and lambda architecture approaches with complex event processing and Process Mining. Thanks to those ideas, we want to design a real time and a posteriori monitoring and surveillance module.

Keywords: Urban Healthcare
Abstract: The assignment and routing problem in Home Service structures is a very complex task, as the provider has to deal with multiple constraints and conflicting objectives. In this paper, we are interesting in the real case problem faced by a Home Service structure in Bourgoin Jallieu, France. Furthermore, we propose a multi-objective model based on a Mixed-Integer Linear Programming. The aim is to minimize the total working time of the staff, to ensure the continuity of care and to balance workload of the staff. Additionally, time windows, qualifications and working time requirements have to be considered. Computational experiments are conducted on a set of instances based on real-life data.

Keywords: Urban Healthcare, eHealth, Complexity modelling
Abstract: Medico-social sector includes a wide range of institutions and services to support vulnerable people. This sector has to ensure personalized support to meet the needs of each person in demand, and also faces a lack of coordination between actors that receive and accompany those people. The orientation process for people with disabilities aims to propose to each person a list of institutions based on their needs. Currently, this orientation process faces many difficulties, and leads sometimes to situations where the person remain without any support. The objective of this document is to present a method to create a process model based on autonomous actors, who have different points of view. This method is applied in modelling the orientation process for people with disabilities within the French context. It seeks to highlight interactions between actors and how the behaviour of each actor affects the whole process. At the same time, it seeks to identify the points of improvement within the behaviour of each actor in order to positively influence the entire orientation process toward the proposition of a more adapted offer to the person.

Keywords: Complex Adaptive Systems, Systems Theory
Abstract: Nowadays, Systems of Systems (SoS) are being more recognised for their importance, they exist across multiple domains, and thus multiple visions of what are they and how they are used. Despite this diversity of definitions, one that is based on their characteristics by Maier (Maier (2005)) is getting more acceptance. Traditional engineering is not enough to address the challenges of SoS because of their complexity, the solution however to build and manage SoS is through an architecture framework that contains the “invariants” of the SoS in question, and the set of rules that manage the interactions between components.

Keywords: Urban Mobility, Supply Logistics
Abstract: The urban freight transport is almost exclusively carried out by truck. Beyond the drawbacks caused in the city, this transport mode is nearly saturated. This paper discusses an alternative way of transporting freight by using urban rail infrastructure in presence of disturbances. In fact, the transport plan of goods using passenger rail network should be updated in accordance with changes that could be occur. These changes deal with different parameters as new transport demands or cancelling of old ones… An initial plan has been proposed using a MILP model for the problem of assigning different predefined transport demand to trains during a given period. In the present paper, dynamic approach based on a rolling horizon is proposed in order to update the initial plan. The updated plan allows to determine a new assignment of changed demands such as the modifications from the previous plan are minimized.

Keywords: Adaptive system and control, Nonlinear adaptive control
Abstract: In this paper, we propose a fractional order adaptive backstepping control solution to the saturation problem of incommensurate fractional order system with uncertainty and nonlinearity. A model transformation is introduced to make the system appropriate to backstepping scheme, and the virtual signals are generated to compensate saturation via the construction of fractional order auxiliary system. By indirect Lyapunov method, the backstepping procedure is applied to fractional order systems with input saturation for the first time, which achieves the goals of stabilization and tracking. Finally, the effectiveness of the proposed fractional order backstepping is demonstrated in several examples.

Keywords: Adaptive system and control
Abstract: An ancient topic as this paper focuses on, some innovative insightful interesting observations are surely provided. On one hand, by expanding the range of integration order in Riemann-Liouville derivative and Caputo derivative, a new type of definitions are given for fractional order derivatives. On the other hand, a novel representation based on Taylor series is formulated, which is helpful to unravel some uncanny feature and handle some hard issues. The advantage of the proposed results lies in that a deeper understanding of fractional order calculus is achieved and it facilitates the relevant application.

Keywords: Model reference adaptive control, Adaptive system and control, Adaptive control -applications
Abstract: Based on factorization of high frequency gain (HFG) matrix K_p, a novel fractional order composite model reference adaptive control (FO-CMRAC) is investigated for a class of fractional order MIMO systems. By introducing K_p=SDU, the stringent symmetry assumption related with the plant high frequency gain matrix is removed. Besides, with the aid of fractional order tracking differentiator (FOTD), the parameter estimation errors is obtained to construct the fractional order parameter updating laws, which can improve the tracking performance. In addition, both the convergence of closed-loop control systems and parameters estimation are proven by indirect Lyapunov approach. Finally, two numerical examples are presented to illustrate the effectiveness of the proposed approach.

Keywords: Adaptive control by neural networks, Identification for control
Abstract: In this paper, new neural filter (NF) based integrator (NF-I) is developed for virtual flux (VF) esti-mation in direct power control (DPC) of a three-phase pulse width modulation (PWM) rectifier. The main advantages of the proposed NF-I are its simple structure, accuracy and provides fast VF esti-mation compared to the traditional first order low-pass (FOLP) filter. The NF capability to online filtering distorted signals is exploited for extracting fundamental components of VF obtained from a pure integration. Numerical simulations of the proposed NF-I inserted in the VF based DPC (VF-DPC) are carried out under different grid voltage conditions. Steady state and dynamic performanc-es of the NF-I are compared with those obtained with the traditional FOLP filter. Simulation results illustrate good performances of the NF-I inserted in the VF-DPC strategy.

Keywords: Switching control, Nonlinear adaptive control
Abstract: The paper proposes a new Variable Structure System (VSS) control algorithm and its application in underwater robotics. The main features of the proposed approach consist on the usage of coupled switching surfaces, and on the usage of an adaptive adjustment method for their parameters in order to accelerate the transient processes. The adaptive algorithm of linear and nonlinear switching surfaces coefficients, is based on the stabilization of the sliding mode parameter close to the reference value. In this paper, it is shown how the proposed approach improves the system transient processes and the energy efficiency in comparison with conventional VSS, neutralizing also some drawbacks. The proposed adaptive VSS algorithm is applied to control a Remotely Operated Vehicle (ROV), and simulation results confirm the advantages to apply it.

Keywords: Adaptive system and control, Adaptive control -applications, Nonlinear adaptive control
Abstract: In this paper we address the problem of parameter estimation performance enhancement for Duffing-like chaotic oscillator with parametric uncertainties. The Dynamic Regressor Extension and Mixing (DREM) approach, which has been recently proposed by the authors, is proven to be a powerful tool in transients improvement; however, it was never applied before for chaotic systems. Here we elaborate on how the DREM approach can be applied for the parameter reconstruction problem of chaotic signal generator used in the data transmitting scenario. The set of numerical examples illustrates the bene ts of the proposed approach.

Keywords: Nonlinear adaptive control, Adaptive system and control
Abstract: This paper proposes a nonlinear controller for Voltage Source Inverter (VSI) used in microgrids. The controlled system includes the VSI, an LC filter, a coupling inductor, and loads. The controller is designedon the basis of the averaged system model, using the backstepping technique and the droop control method. The controller stability is theoretically analyzed and its performances are illustrated by simulation in different grid operation modes(connected and islanded)and load changes.

Keywords: Adaptation and learning in physical agents, Multi-agent systems, Coordination of multiple vehicle systems
Abstract: This paper presents a novel approach to artificial situation awareness for an autonomous vehicle operating in complex dynamic environments populated by other agents. A key aspect of situation awareness is the use of mental models to predict future states of the environment, allowing safe and rational routing decisions to be made. We present a technique for predicting future discrete state transitions (such as the commencement of a turn) by other agents, based upon an uncertain mental model. Predictions take the form of univariate Gaussian distributions, which capture the inherent uncertainty in transition time, whilst still providing great benefit to a decision making system. The prediction distributions are compared with Monte Carlo simulations and show an excellent correlation over long prediction horizons.

Keywords: Model reference adaptive control, Adaptive system and control, Nonlinear adaptive control
Abstract: This work proposes a novel switched model reference adaptive control (MRAC) architecture, ensuring parameter convergence without requiring the assumption of persistence of excitation (PE). Previous results which ensure parameter convergence with PE suffer from the disadvantage that the condition cannot be verified online as it relies on the future behaviour of the signal. Further, the PE requirement is often imposed by adding perturbation in the reference/input signal, which may deteriorate tracking performance, and thus renders the objectives of control and identification conflicting to each other. Unlike PE, this work ensures parameter convergence by imposing a newly defined, significantly milder, and online verifiable initial excitation (IE) assumption. A switched composite parameter estimator is designed with the help of two layers of low pass filters, where the first layer obviates the need for state derivative knowledge and the second layer along with the switching term in the estimator relaxes the PE condition. Provided the IE condition is satisfied, the proposed design guarantees uniform global exponential stability (UGES) of the error dynamics, where the convergence rate is user-assignable.

Keywords: Adaptive system and control, Model reference adaptive control, Identification for control
Abstract: The output adaptive tracking problem for a class of linear time-invariant plants with known parameters, unmeasurable state and arbitrary input delay is considered. The plant high frequency gain and its sign are uncertain. The reference signal is represented by multi-sinusoidal function of time generated by autonomous linear dynamical system of known order but with unknown parameters. The proposed adaptive control law is based on modification of augmented error approach that allows to “swap” the delay and cope with high frequency gain with unknown sign. The designed adaptive control law ensures boundness of all signals in the closed-loop system and asymptotical convergence of tracking error to zero.

Keywords: Adaptive control -applications, Subspace methods, Identification for control
Abstract: Experimental identification of the modal state-space model for Active Vibration Control (AVC) is proposed based on Subspace Identification Method (SIM). A stress-ribbon bridge built at the Technische Universität Berlin was taken as research object. A real-time control system with pneumatic muscle actuators and inertial sensors was set up for AVC of the bridge. For the purpose of AVC, the feedback control design requires a modal state-space model, which describes the multi-modal characteristics of resonance modes of the bridge and the input/output relationship of the controlled system. Analytically, a state-space model of the bridge can be derived from Euler-Lagrange mechanism. However this is computationally expensive and the determination of damping ratios is also inconvenient. Comparably, SIM offers an attractive alternative due to simple and general parametrisation for Multiple-Input Multiple-Output (MIMO) systems. The identified state-space model from SIM can easily be transformed into a reduced modal state-space model for the AVC controller design. The goodness of the identified state-space model and the truncated modal state-space model was investigated in the stabilization diagram of SIM and with model fit indexes. The identified modal parameters of the footbridge from SIM were compared with that of previous free-vibration tests and the analytical model. Implementation of a Delayed Modal Velocity Feedback Control (DMVFC) based on the obtained modal state-space model was carried out for the full-scale lightweight bridge. The effectiveness of the proposed experimental identification method was shown in case of vertical resonance modes in vibration control experiments.

Keywords: Iterative learning control, Adaptive control -applications, Identification for control
Abstract: In this paper, an adaptive optimal control scheme based on parameter estimation is proposed for optimal control problem of servomechanisms with unknown parameters. Parameters of the servomechanism dynamics are identified online first. Based on parameter estimation, the optimal control policy is achieved through adaptive dynamic programming.The estimation removes an approximation structure from the original method. Therefore the number of unknown weights in approximation structures, to be calculated, is reduced. The analysis for convergence is presented to prove the validity. Finally, simulation results demonstrate that the scheme can approximate the optimal control policy rapidly and effectively.

Keywords: control of hyperbolic systems and conservation laws, Lyapunov methods, stability of distributed parameter systems
Abstract: The paper is concerned with the PI control regulation of a star-shaped network of systems governed by hyperbolic partial differential equations. The control input and measured output are on the boundary. First, each system of the network is linearized and diagonalized with Riemann invariants. Then, by using Lyapunov direct method, the PI controller is proposed for a single system. Finally, we extend the PI control design for the star-shaped network of n subsystems. The exponential stability and output regulation of closed-loop systems are all proven with the aid of a strict Lyapunov functional

Keywords: controllability and observability of distributed parameter systems
Abstract: In this paper, the optimal sensor location problem is first discussed for environmental monitoring of physical phenomena governed by some advection-diffusion partial-differential equations. In particular, the exact derivation of the observability Gramian of an advection-diffusion PDE is investigated. Based on the optimality criteria derived from this analysis, a law conservation governing the behavior of a crowd of mobile sensors is proposed to ensure convergence of the sensor density towards an optimal location. The monitoring of pollution on a 2D domain is the case study used throughout the paper to illustrate the effectiveness of the proposed approach.

Keywords: system identification and adaptive control of distributed parameter systems, control and estimation of wave equations and systems of elasticity, Systems biology
Abstract: In this paper, a method based on modulating functions is proposed to estimate the Cerebral Blood Flow (CBF). The problem is written in an input estimation problem for a damped wave equation which is used to model the spatiotemporal variations of blood mass density. The method is described and its performance is assessed through some numerical simulations. The robustness of the method in presence of noise is also studied.

Keywords: control of hyperbolic systems and conservation laws, backstepping control of distributed parameter systems, stability of distributed parameter systems
Abstract: We give sufficient conditions that guarantee exponential stability for an uncertain system of two coupled linear hyperbolic PDEs with the actuation proposed in (cite{vazquez2011local}) applied at one boundary of the system. Using the backstepping approach, we map the original uncertain system to a system with a simpler structure. Using the Lyapunov approach proposed in~(cite{bastin2011boundary,diagne2012lyapunov}) it is then possible to derive sufficient conditions that guarantee robustness. Using the same target system we derive a simple algorithm that ensures robust output tracking.

Keywords: stability of delay systems, Systems with time-delays, Descriptor systems
Abstract: Problem of constructing finite-dimensional stabilizing controllers for a class of linear time-invariant neutral time-delay systems, namely lossless propagation time-delay systems, is considered while the effect of small time-delay perturbations on stability is taken into account. For this purpose, a dynamic output feedback controller design approach which provides more flexible and automated design of the controller than previously proposed design approaches based on the continuous pole placement algorithm is proposed. A design example is also presented, to demonstrate the proposed approach.

Keywords: stability of delay systems, Robust control (linear case), Robust time-delay systems
Abstract: One of the most significant limitation of the productivity of machining operations is the regenerative machine tool vibration, also called machine tool chatter, which is a selfexcited vibration between the tool and the workpiece induced by the chip formation mechanism. Extension of the chatter-free parameters is possible by active chatter control techniques. The design of the controller requires the identification of the dynamic properties of the system. Uncertainties in the system parameters may result in an inappropriate control performance. Robust control design is therefore a necessary step during the optimization of machining operations. In this paper, a fast and efficient method is presented to determine the region of control gains in the presence of uncertainties in the measured frequency response functions. The method is based on the concept of structured singular values.

Keywords: control of heat and mass transfer systems, Infinite-dimensional systems, backstepping control of distributed parameter systems
Abstract: This contribution introduces a full-state boundary feedback for cylindrical heat conductors. The desired decay properties are imposed to the spectrum of linear, second-order parabolic partial differential equations (PDEs). The feedback-scheme exploits periodicity in angular direction for cylindrical coordinates to reduce the 3-dimensional (3-D) system to a set of 2-D subsystems by means of a Fourier transformation. A backstepping-based controller for shifting the spectra for each of the decoupled systems on 2-D domains is presented. It can be shown, that any decay rate of the overall tracking error can be achieved by superposing solely a finite number of these controllers. The validity of the approach is shown by simulations.

Keywords: stability of distributed parameter systems, Constrained control, Passivity-based control
Abstract: The main aim of this paper is to address the global asymptotic stabilization (GAS) of a class of dissipative partial differential equations (PDEs) via finite-dimensional admissible (regular and bounded) damping (output) controls. To this end, we use the inertial manifold theory to derive infinite-dimensional dissipative control systems given by interconnection of a finite-dimensional control system on the inertial manifold plus an infinite-dimensional zero-input system on the complement. We show that the GAS of such systems is reduced to the finite-dimensional one. Then, we prove that the finite-dimensional systems which are zero-input point-dissipative (have global attractors K) and those which are B-strictly passive (passivity relative to bounded sets) are connected. Finally, we use the control Lyapunov functions (CLF) theory to design admissible feedback damping controls for the GAS of B-strictly passive systems.

Keywords: port Hamiltonian distributed parameter systems, control of hyperbolic systems and conservation laws, model reduction of distributed parameter systems
Abstract: This paper deals with the structure and passivity preserving model reduction and the reduced order controller design for a class of distributed controlled port Hamiltonian systems--Timoshenko beam. The boundary conditions of the beam lead to physical constraints which are hardly considered in the reduction procedure. In this work we propose to use the descriptor system realization of port Hamiltonian system to conserve the physical constraints. A passive LQG control design method is proposed for this type of system. This LQG method defines a balanced coordinate which allows us to reduce the system. Using the obtained reduced model, a reduced order passive controller which stabilizes the full order system is designed using the LQG method. At last we give the numerical simulations to show the effectiveness of the proposed reduced passive controller.

Keywords: controllability and observability of distributed parameter systems, control of hyperbolic systems and conservation laws, thermal and process control applications of distributed parameter systems
Abstract: In this work, we consider the estimation of temperature profiles along the pipes of a plate heat exchanger. The transport phenomena through the heat exchanger are modeled by hyperbolic partial differential equations (PDE) of first order in time and space. The counter-flow heat exchange implies that the system is comprised of rightward (where the hot fluid circulates) and leftward (cold fluid pipes) hyperbolic PDE. The heat exchanged between the pipes of hot and cold fluid induces a coupling between the rightward and leftward equations, which increases the difficulty of solving the PDE system. The estimation objective is addressed by the design of an observer using a PDE approach, which uses boundary measurements to estimate the distributed profiles. The convergence of the observation error is established using Lyapunov analysis. Simulation results illustrate the efficiency of our method using a simulator with time-varying parameters validated on experimental data.

Keywords: model reduction of distributed parameter systems, control of heat and mass transfer systems, Descriptor systems
Abstract: A mixed Galerkin formulation for reduced-order modeling is presented for controller design of distributed parameter systems with boundary inputs. A null space approach is established to yield appropriate trial and test functions by using candidate trial functions which are free from boundary conditions.　The approach is applicable, with considerably mild conditions on the candidate trial functions, on the interior domain as well as its boundaries. It is shown that this modeling technique yields a finite dimensional descriptor system of index 1, that is equivalent to a state-space representation suitable for controller design model. Effectiveness of the proposed method is demonstrated by an example of a heat conduction rod using polynomial functions which are not preprocessed to meet the boundary conditions.

Keywords: Sliding mode control, Nonlinear observers and filter design
Abstract: In this paper the problem of state estimation for the Pendulum-Cart System is addressed. Different high-order sliding-modes techniques are applied for such a mechanical system. The mathematical model is studied and a couple of high-order sliding-modes observers are proposed to estimate the state, in spite of disturbances; exactly and in a finite or fixed-time, respectively. Some experiments and comparisons are presented to illustrate the effectiveness of the presented algorithms.

Keywords: Sliding mode control, Stability of hybrid systems, Observers for linear systems
Abstract: Acceleration of estimation for a class of nonlinear systems in the output canonical form is considered in this work. The acceleration is achieved by a supervisory algorithm design that switches among different values of observer gain. The presence of bounded matched disturbances, Lipschitz uncertainties and measurement noises is taken into account. The proposed switched gain observer guarantees global uniform time of convergence of the estimation error to the origin in the noise-free case. In the presence of noise our commutation strategy pursuits the goals of overshoot reducing for the initial phase, acceleration of convergence and improvement of asymptotic precision of estimation. Efficacy of the proposed switching-gain observer is illustrated by numerical comparison with a sliding mode and linear high-gain observers.

Keywords: Sliding mode control, Output feedback control, Robustness analysis
Abstract: In this paper we address the robust tracking control problem, against the unknown but bounded matched disturbances, for an inertia wheel pendulum. The interested periodic motion of the pendulum will be in the upright position which corresponds to an unstable equilibrium point of the unforced system. A two-relay controller based reference model was developed for generating the reference trajectories where a second order sliding modes controller enforces the unactuated link to follow such prescribed trajectory. The desired amplitude and frequency were tuned by choosing the two relay control gains properly. A variable structure observer was developed to estimate the velocity of the pendulum and the wheel. Lyapunov stability analysis was made to demonstrate the robustness of the closed-loop system. Performance issues of the constructed controller-observer were illustrated in a numerical study.

Keywords: Sliding mode control, Robust control applications, Robust control
Abstract: Stabilization of a cart-pendulum system through Higher Order Sliding Mode design is presented. From Singular LQ method, a relationship between order of singularity of a given performance index and the order of sliding mode controller is established. Thus, several arbitrary relative degree optimal sliding surfaces and its corresponding Higher Order Sliding Mode Controller can be specified for a given system. Continuous Higher Order Sliding Mode Controllers are obtained through a robustification method for arbitrary relative degree controllers based on Integral Sliding Modes and Super-Twisting Algorithm. An agreement between the accuracy/complexity of the Continuous Higher Order Sliding Mode Controller and the limited accuracy offered by the system's sensors and actuators is obtained experimentally.

Keywords: Sliding mode control, Robust control, Control of switched systems
Abstract: A two relay controller is robustified by a switched integral sliding mode controller in order to generate robust self-oscillations for pendulum systems. The proposed strategy assures theoretically exact robustification of the self-oscillations preserving the amplitude and frequency of the oscillations even in the presence of matched uncertainties/perturbations. The efficiency of the proposed robustifying approach is illustrated on an example of a Furuta pendulum.

Keywords: Nonlinear predictive control, Input-to-State Stability, Delay systems
Abstract: We investigate input-to-state stabilization for a general nonlinear system with input delay and disturbances. With an infinite-dimensional backstepping transformation, the original system is transferred to a target system. A delay-compensating and disturbances attenuating control law is designed for this kind of nonlinear systems. Stability of the target system is first proved by constructing a Lyapunov functional. Equivalence of norms for original and target system is deduced. Further, input-to-state stabilization for the original system under the delay-compensating control law is drawn.

Keywords: Nonlinear predictive control, Robust control, Control of constrained systems
Abstract: Min-max differential inequalities (DIs) can be used to characterize robust forward invariant tubes with convex cross-section for a large class of nonlinear control systems. The advantage of using set-propagation over other existing approaches for tube MPC is that they avoid the discretization of control policies. Instead, the conservatism of min-max DIs in tube MPC arises from the discretization of sets in the state-space, while the control law is never discretized and remains defined implicitly via the solution of a min-max optimization problem. The contribution of this paper is the development of a practical implementation of min-max DIs for tube MPC using ellipsoidal-tube enclosures. We illustrate these developments with a spring-mass-damper system.

Keywords: Nonlinear predictive control, Stability of nonlinear systems, Lyapunov methods
Abstract: The quasi infinite horizon NMPC formulation developed by Chen and Allgower [1998] provides a systematic method to characterize the terminal set needed to ensure nominal stability of a system controlled using finite horizon NMPC formulation at an unstable operating point. Their approach, however, has been developed for continuous time NMPC formulations. Real time implementation of an NMPC scheme using microprocessors, however, makes model discretization inevitable. In this work, a discrete time version of the quasi infinite NMPC formulation is developed, which is particularly suited for operating a system at an unstable operating point. Also, a novel approach is developed for characterization of the terminal region that makes use of the discrete time nonlinear model and that provides sufficient degrees of freedom to characterize the terminal region. The nominal closed loop system is then shown to be equi-asymptotically stable when controlled using the proposed discrete time QIH-NMPC. Efficacy of the proposed approach is demonstrated using a benchmark problem given by Chen and Allgower [1998]. The simulation study shows that the proposed approaches result in terminal regions that are comparable or larger than the terminal region reported by Chen and Allgower [1998]. Also, the proposed discrete time QIH-NMPC is able to steer the state trajectories from specified feasible initial conditions to locations inside the terminal set within the specified prediction horizon and later converge to the unstable operating point.

Keywords: Nonlinear predictive control, Process control, Control design for hybrid systems
Abstract: This paper presents a new algorithm for the predictive control of systems with on-off actuators that it is tailored for systems in which part of the state vector depends only slightly on past values of the control signal beyond a certain t-L time instant. An example of this is a system with both slow and fast stable dynamics, where the fast ones vanishes after a certain time while the slow dynamics are still influencing the transient state. The algorithm is based on an iterative procedure that constructs a set of candidate solutions to the predictive control problem. The size of the candidate solutions set is reduced from 2^N to an user specified value M that can be set accordingly to the computing capabilities of the machine in which the algorithm is to be implemented. The algorithm considers nonlinear systems and although the solution is suboptimal, the approximation error is small in practice and reduces with higher M values. The results are illustrated with a simulated example.

Keywords: Control of interconnected systems, Constrained control, Decentralized control
Abstract: This paper proposes a distributed model predictive control algorithm for vehicle platooning and more generally networked systems in a chain structure. The distributed models of the vehicle platoon are coupled through the input of the preceding vehicles. Using the principles of robust model predictive control, the coupled input is regarded as a disturbance and the robust model predictive control algorithm proposed by [Kerrigan, 2001] is employed for every vehicle. Based on this approach, a new distributed model predictive control algorithm is proposed by communicating the inputs among the vehicles, which enlarges the feasible regions of the local controllers while recursive feasibility still holds.

Keywords: Lyapunov methods, Control in neuroscience, Application of nonlinear analysis and design
Abstract: We introduce an asymptotically stable nonlinear controller for a two-muscle system with an agonist-antagonist arrangement. The classical Hill model with series and parallel elasticity is used for each muscle. The controller is based on a combination of backstepping and algebraic virtual control matching to determine final activation control signals. Two definitions for the synthetic input used in the first backstepping stage are considered, a scalar form and a vector form. A novel feature of the vector approach is the ability to incorporate a minimum-effort optimality criterion as a way of resolve actuation redundancy. Minimum effort criteria reflect well-established biomechanical principles of human movement. The proposed approach is scalable and can serve as a ``working controller'' to facilitate studies in the field of human-machine interactions, including machine control systems and biomechanical state estimation.

Keywords: Lyapunov methods, Evolutionary algorithms, Control of constrained systems
Abstract: This paper presents an automatic controller synthesis method for nonlinear systems with reachability and safety specifications. The proposed method consists of genetic programming in combination with an SMT solver, which are used to synthesize both a control Lyapunov function and the modes of a switched state feedback controller. The resulting controller consists of a set of analytic expressions and a switching law based on the control Lyapunov function, which together guarantee the imposed specifications. The effectiveness of the proposed approach is shown on a 2D pendulum.

Keywords: Control of interconnected systems, Distributed nonlinear control, Control under communication constraints (nonliearity)
Abstract: Fixed-point iterations are commonly used to break the algebraic loops involved in the distributed optimization among computational entities sharing only a partial knowledge. However, although this approach is appealingly simple and that it works astonishingly well in many practical situations, its use is rarely associated to an appropriate analysis of its convergence. In this paper, it is shown that this iteration can be rationally conducted using control theory in order to derive a provable stability under appropriate assumptions.

Keywords: Lyapunov methods, Stability of nonlinear systems, Input-to-State Stability
Abstract: The input-to-state stability property of nonlinear dynamical systems with multiple invariant solutions is analyzed under the assumption that the system equations are periodic with respect to certain state variables. It is shown that stability can be concluded via a signindefinite function, which explicitly takes the systems’ periodicity into account. The presented approach leverages some of the difficulties encountered in the analysis of periodic systems via positive definite Lyapunov functions proposed in Angeli and Efimov (2013, 2015). The new result is established based on the framework of cell structure introduced in Leonov (1974) and illustrated via the global analysis of a nonlinear pendulum with a constant persistent input.

Keywords: Control of systems in vehicles, Guidance, navigation and control of vehicles, Space exploration and transportation
Abstract: A cold gas propulsion system is well suited to provide the required thrust for a small surveyor spacecraft operated near an asteroid or planetary surface. The cold gas propellant can obtained in-situ from local surface or atmospheric constituents. For small spacecraft, the cold gas system may be limited to only on-off control of the main tank where the generated thrust is directly dependent on the tank pressure. As such the thrust will slowly decrease as the propellant is expended. A state feedback, time optimal, control law is developed for a vehicle with decreasing thrust in translational motion. The success of the control law is shown in simulation.

Keywords: Guidance, navigation and control of vehicles, Control of systems in vehicles, Autonomous systems
Abstract: The present article proposes a predictive control law for orbital spacecraft rendezvous hovering phases. An innovative description of periodic space-restricted trajectories based on computing the envelope of a family of curves is given. This description is used to provide a model predictive controller able to minimize the fuel consumption and account for convex constraints, such as periodicity, saturation of the thrusters and space restrictions. The efficiency of this control algorithm is assessed on a board simulating the performance of devices usually employed in space applications.

Keywords: Guidance, navigation and control of vehicles
Abstract: This paper presents a new minimum-fuel glideslope guidance algorithm for approaching a target evolving on an elliptic orbit. In addition to the usual rectilinear profile to follow as in Hablani’s seminal paper, two new features are requested for the new algorithm. The first one imposes bounds on the guidance error inherent to chemical propulsion glideslope guidance, such that the chaser’s trajectory does not escape from an admissible domain. The second one minimizes the consumption during rendezvous. Indeed, unlike the classical glideslope algorithm for which there is no direct control on the fuel consumption, additional degrees of freedom and relevant decision variables may be identified. By combining a useful parametrization of the Tschauner-Hempel relative equations of motion and results from polynomial optimization, a semidefinite formulation of the constraints on the maximal guidance error is obtained. For a fixed-time glideslope rendezvous with a pre-assigned number of maneuvers, a fuel-optimal solution with a bounded guidance error is obtained by solving a semidefinite programming problem. Two numerical examples illustrate the usefulness of the method compared to the classical ones when the approach corridor has to verify stringent geometrical restrictions such as line-of-sight constraints.

Keywords: Man-in-the-loop systems, Autonomous systems, Mission control and operations
Abstract: In each mission phase, a satellite is characterized by a well-defined set of modes. They define a clear configuration of the spacecraft subsystems and have specific operational implications. In this paper, we present an approach for geostationary earth observation satellite mode management during both the Launch and Early Orbit phase and the full operational phase. It draws on a real space mission project currently carried out at OHB System AG. The configurations of the Attitude and Orbit Control System are also analyzed, their operational meaning and the relationship with the satellite modes. It is also explained how on-board autonomy requirements play a relevant role in the satellite mode definition and management. Geostationary satellites can usually be operated in a quasi real-time fashion, therefore a limited level of on-board autonomy can be sufficient. However, they can be characterized by high availability requirements and have a need for ground operation reduction, which can lead to an increased level of on-board autonomy in satellite mode management.

Keywords: Flight dynamics identification, formation flying, Guidance, navigation and control of vehicles, Space exploration and transportation
Abstract: Focused on the removal of space debris, this paper studies the modeling of a target satellite connected to a chaser satellite by a tether. All dynamic couplings between the flexible and rigid modes of the satellites are accounted for. The tether attached to both satellites is modeled as a massless spring when stretched and non-existent when compressed. The objective of this work is to model the behaviour of the three bodies: chaser, tether, and target in the orbital reference frame for arbitrary initial conditions of the target satellite. Simulations of the whole system including the chaser Attitude and Orbit Control System (AOCS) are performed to evaluate its ability to damp the debris tumbling motion and to tow the debris.

Keywords: Health monitoring and diagnosis, Decision making and autonomy, sensor data fusion, Autonomous systems
Abstract: This paper presents a novel scheme for the detection and isolation of faults affecting the sensors measuring the satellite attitude, body angular velocity and flywheel spin rates as well as defects related to the control torques provided by satellite momentum wheels. Thanks to the jointly use of the singular perturbations theory and nonlinear geometric approach, a novel fault detection and isolation system has been developed to accurately detect and isolate faults occurring on all the considered actuators and sensors. Simulation results are based on a detailed nonlinear satellite model with embedded disturbance description. The results document the effectiveness of the proposed fault detection and isolation scheme.

Keywords: Model-driven systems engineering
Abstract: With systems being more and more complex, especially in the case of Nuclear Power Plant design, Systems Engineering (SE) has seen an increasing interest in the industrial world. Although SE concepts and processes have become well-known, passing from Requirements to Functional Architectures has not been a fully addressed issue. This paper proposes a tooled method that offers three different design perspectives: a Requirement View, a Context View and a Behavioural View. Those views mainly help the designers to express requirements, structure their architecture design, work together, verify and partially validate their design by means of five interconnected Design Specific Modelling Languages (DSML).

Keywords: Modelling and decision making in complex systems, Business process management systems, Enterprise integration
Abstract: This article proposes an integrated process that combine Systems Engineering processes and Project Management ones. These processes are defined according to the industrial standard processes existing in the literature. The main idea is to define a common information model enabling the federation of all the points of view of the different actors with regards to Systems Engineering, Project Time Management, Project Cost Management and Project Risk Management. The resulting integrated project graph encompasses all the scenarios established after defining all the coupling points between those processes. The definition of the graph is based also on the available knowledge and the capitalized experiences resulting from experience feedback on previous projects. The scenario selection optimization is then performed using a decision-aided tool that aims to build a panel of Pareto-optimal solutions taking into account uncertainties on project objectives (cost and duration). This tool will also enable the decision-maker to select one scenario according to an acceptable level of risks. The integrated process, the optimization tool based on Ant Colony Optimization (ACO) and the method for decision making are described in the paper.

Keywords: Model-driven systems engineering, Modelling and decision making in complex systems
Abstract: This paper deals with the management of business rules and requirements to be integrated to a PLM system during the SE process. It proposes a rule and requirement management process made of four stages: the expression of the rule, the activation of the rule, the application of the rule and the checking of the requirement. To support this process, a generic meta-model is presented. The proposed model is called DALTON for ``DAta Linked Through Occurrences Network" because it is based on a data network. The model is validated with a use case taken from the nuclear industry, and algorithms in Java were developped to implement the associated reasoning automating the process of rules and requirements engineering.

Keywords: Model-driven systems engineering, Methodologies and tools for analysis of complexity
Abstract: In the nineties the growing integration of electronic components in mass products led to the introduction of systems engineering methods in the design offices. In the automotive industry this deployment has been accelerated due to the need for the reduction of polluting emissions and for safety concerns. Recently the introduction of safety standards such as ISO 26262 and the design of connected and autonomous vehicles required the development of new system modeling approaches, and particularly, model-based safety analysis methods (MBSA). In this article, we explain how Functional Safety Concept can be determined jointly with the definition of the logical architecture. This will be based on failure propagation mechanisms. This method is applied on an automotive case study.

Keywords: Modelling and decision making in complex systems, Business process management systems, Complex logistic systems
Abstract: Urban freight transportation plays a pivotal role in ensuring the liveability of urban areas due to its fulfilment of citizens needs and its induced economic impact. Building upon the body of research on the topic of city logistics, its connected impacts and measures, this paper focuses on the development of a framework which is collectively exhaustive in describing the concerning crucial elements and in revealing their multiple and mutual influences. Through the investigation of an academic definition of ecosystem, its decipherment in terms of urban logistics followed by its application to case studies, such a framework has been firstly theoretically designed and then some application examples are given.

Keywords: Modelling and decision making in complex systems, Model-driven systems engineering
Abstract: In order to respond to a call for tenders, bidders must define and evaluate potential solutions, based upon the specifications of customer’s requirements and their capabilities (skills, existing solutions, resources … etc.). The definition and the evaluation of potential solutions are not trivial activities. The lack of relevant information makes the evaluation imprecise and uncertain. Therefore bidders choose the most suitable solution based upon the standard indicators (cost, performance and lead time) and their subjective feeling. Unfortunately, this may leads to the choice of unfeasible solution regarding customer’s expectations (cost, performance and delivery time). Therefore, the aim of this paper is twofold: (i) first, to clarify the notion of imprecision and uncertainty in the evaluation of potential solutions; and (ii) second, to propose two Confidence Indexes (CI) in order to take into account uncertainty in offer elaboration. The first one (CIS) characterizes the confidence in the technical system solution and the second one (CIP) the confidence in the implementation process of the technical system. The proposed CIS and CIP will enable bidders to choose the most relevant solution not only based upon the standard indicators but also considering the confidence in the potential solutions.

Keywords: Identification for control, Continuous time system estimation, Time series modelling
Abstract: Considerable effort has been devoted to the development of algorithms for identification of parsimonious discrete time models from noisy input/output data sets since this facilitates controller design. Several methods, such as nuclear norm minimization, have been used to provide approximate solutions to this non-convex problem. However, even though the field of continuous time system identification is now mature, results on parsimonious model identification of continuous time systems are still very limited. In this paper, an atomic norm minimization method is proposed for this purpose that can handle non-uniformly sampled data without preprocessing. The proposed approach provides an efficient way to use noisy, non-uniformly sampled data to determine a reliable, low-order continuous time model. Numerical performance is illustrated using academic examples and simulated behavioral data from a smoking cessation study.

Keywords: Fault detection and diagnosis, Input and excitation design
Abstract: The paper deals with an active fault detection problem for jump Markov nonlinear systems with Gaussian noises. The problem is formulated as a functional optimization problem over an infinite-time horizon with a general discounted detection criterion. The design of an active fault detector is performed in two steps. First, the original problem is recast as a perfect state information problem by complementing the nonlinear system with a suboptimal state estimator based on a bank of extended Kalman filters. Then, a temporal-difference learning algorithm is used to train the active fault detector such that the criterion is minimized. A simulation example of a differential wheeled robot is used to illustrate the performance of the proposed design.

Keywords: Fault detection and diagnosis, Input and excitation design, Particle filtering/Monte Carlo methods
Abstract: In this paper, a problem of active fault diagnosis for jump Markov nonlinear systems with non-Gaussian noises is considered. The imperfect state information formulation is transformed using sufficient statistics to a dynamical optimization problem that can be solved using approximate dynamic programming. The sufficient statistics are produced using the Bayesian recursive relations and particle filter algorithm. A special structure of approximate Bellman function is chosen to reduce a complexity caused by high dimension of statistics obtained from the particle filter. The proposed active fault detector design is compared with an extended Kalman filter based design in the simulation example.

Keywords: Identification for control, Closed loop identification, Nonlinear system identification
Abstract: This paper examines the problem of estimating the parameters of a combined thermal and electrochemical model of a lithium-ion battery from a single non-invasive, dynamic experiment. This paper is motivated by the poor parameter identifiability suffered by the models needed for model-based control of lithium-ion batteries. There is already a substantial literature on battery parameter estimation, but most research conduct separate studies for thermal and electrochemical parameter estimation. The goal in this paper, in contrast, is to examine the feasibility of estimating both sets of parameters simultaneously, from a single experiment. We focus, in this feasibility study, on reduced-order models to simulate both the thermal and electrochemical dynamics. However, the underlying approach is extendible to higher-order representations. An optimal battery cycling is designed to maximize the Fisher identifiability of the combined model's parameters, namely the battery’s charge capacity, ohmic resistance, diffusion-related resistance/capacitance eigenvalues, entropy coefficients as a function of state of charge, and thermal time eigenvalue. The current trajectory maximizing the identifiability of the thermal and electrochemical parameters is validating through a Monte Carlo simulation study. This study shows that this framework can indeed enable the accurate simultaneous estimation of all of the above parameters based on a single experiment lasting just 12 hours. The results are encouraging considering the laboratory time needed for estimating these parameters using separate thermal/electrochemical identification experiments.

Keywords: Input and excitation design, Identification for control
Abstract: A new optimization-based approach to experiment design for dynamic MIMO identification is presented. Unlike previously proposed methods that consider dynamics and constraints, the proposed method directly addresses the distribution of output data to be generated in the experiment. The problem is formulated as a convex optimization problem with constraints expressed as linear matrix inequalities (LMIs). Two optimization objectives considered are to maximize the smallest singular value and the determinant of the output covariance matrix. The solution can be implemented in a similar way as previously proposed gain-directional designs based on an estimate of the static gain matrix. The type of perturbation (e.g., RBS, PRBS, multisine signal) can be selected by the user. Various aspects of the method are illustrated by the Wood-Berry distillation column.

Keywords: Nonlinear system identification, Identification for control
Abstract: An automatic order determination and input selection method for nonlinear dynamic models following the external dynamics approach is proposed. Based on a wrapper- like input selection approach using local model networks (LMN), the proposed method is able to automatically identify important operating point (OP) variables solely based on measured data. If local linear models are used, the OP variables describe regions in which the process can sufficiently be described by linear, dynamic models. The necessary order of these linear, dynamic models is determined altogether with the OP variables in one framework by the proposed method. We show that this method is able to improve the model accuracy and lead to a more concise model for a real-world heating, ventilating and air conditioning (HVAC) system.

Keywords: Fault detection and diagnosis, Multi-agent systems, Hybrid and switched systems modeling
Abstract: The ability to detect topology variations in dynamical networks defined by differential algebraic equations (DAEs) is considered. We characterize the existence of initial states, for which topological changes are indiscernible. A key feature of our characterization is the ability to verify indiscernibility just in terms of the nominal topology. We apply the results to a power grid model and also discuss the relationship to recent mode-detection results for switched DAEs.

Keywords: Estimation and filtering, Sensor networks, Control and estimation with data loss
Abstract: This paper studies a remote state estimation problem in the presence of an eavesdropper. A sensor transmits local state estimates over a packet dropping link to a remote estimator, which at the same time can be overheard by an eavesdropper with a certain probability. The objective is to determine when the sensor should transmit, in order to minimize the estimation error covariance at the remote estimator, while trying to keep the eavesdropper error covariance above a certain level. This is done by solving an optimization problem that minimizes a linear combination of the expected estimation error covariance and the negative of the expected eavesdropper error covariance. Structural results on the optimal transmission policy are derived, and shown to exhibit thresholding behaviour in the estimation error covariances. In the infinite horizon situation, it is shown that with unstable systems one can keep the expected estimation error covariance bounded while the expected eavesdropper error covariance becomes unbounded.

Keywords: Cooperative systems
Abstract: A secure and private framework for inter-agent communication and coordination is developed. This allows an agent, in our case a fleet owner, to ask questions or submit queries in an encrypted fashion using semi-homomorphic encryption. The submitted query can be about the interest of the other fleet owners for using a road at a specific time of the day, for instance, for the purpose of collaborative vehicle platooning. The other agents can then provide appropriate responses without knowing the content of the questions or the queries. Strong privacy and security guarantees are provided for the agent who is submitting the queries. It is also shown that the amount of the information that this agent can extract from the other agent is bounded. In fact, with submitting one query, a sophisticated agent can at most extract the answer to two queries. This secure communication platform is used subsequently to develop a distributed coordination mechanisms among fleet owners.

Keywords: Estimation and filtering, Sensor networks
Abstract: We consider the problem of estimating the state of a linear time-invariant Gaussian system in the presence of sparse integrity attacks. The attacker can control p out of m sensors and arbitrarily change the measurements. Under mild assumptions, we can decompose the optimal Kalman estimate as a weighted sum of local state estimates, each of which is derived using only the measurements from a single sensor. Furthermore, we propose a convex optimization based approach, instead of the weighted sum approach, to combine the local estimate into a more secure state estimate. It is shown that our proposed estimator coincides with the Kalman estimator with certain probability when all sensors are benign, and we provide a sufficient condition under which the estimator is stable against the (p,m)-sparse attack when p sensors are compromised. A numerical example is provided to illustrate the performance of the proposed state estimation scheme.

Keywords: Distributed control and estimation, Sensor networks
Abstract: This paper studies linear time-varying (LTV) network systems aected by multiple unknown inputs. The goal is to reconstruct both the initial state and the unknown input. The main result is a characterization of strong structural input and state observability,i.e., the conditions under which both the whole network state and the unknown input can be reconstructed for all system matrices that share a common zero/non-zero pattern. This characterization is in terms of strong structural observability of a suitably-de ned linear timeinvariant (LTI) subsystem.

Keywords: Fault detection and diagnosis, Control over networks, Channel estimation/equalisation
Abstract: This paper addresses the detection and isolation of replay attacks on sensor measurements. As opposed to previously proposed additive watermarking, we propose a multiplicative watermarking scheme, where each sensor’s output is separately watermarked by being fed to a SISO watermark generator. Additionally, a set of equalizing filters is placed at the controller’s side, which reconstructs the original output signals from the received watermarked data. We show that the proposed scheme has several advantages over existing approaches: it has no detrimental effects on the closed-loop performance in the absence of attacks; it can be designed in a modular fashion, independently of the design of the controller and anomaly detector; it facilitates the detection of replay attacks and the isolation of the time at which the replayed data was recorded. These properties are discussed in detail and the results are illustrated through a numerical example.

Keywords: Modeling for control optimization, Data-based control, Parametric optimization
Abstract: The generation of fuzzy rules from samples is significant for fuzzy modelling. To improve the robustness of Wang-Mendel (WM) method, an improved WM method to extract fuzzy rules from all the regularized sample data was proposed. However, the accuracy of the model with this method is degraded for the conflicting rules with small difference between support degrees. And the output subsets can only be chosen from the pre-defined ones. To solve these problems, we develop an improved-WM method based on optimization of centers of output fuzzy subsets for fuzzy rules (COiWM). This method adopts the fuzzy c-means (FCM) clustering algorithm to divide the input and output spaces, and the improved WM method which replaces the original data by regularized data is used to calculate the support degrees. Then the support degrees are used as weights to optimize the centers of output fuzzy subsets with a method of weighted averages, so as to enhance the accuracy of a fuzzy model. Experimental results of a case study on short term daily maximum electric load forecasting prove that our proposed method enhances the accuracy of a fuzzy model.

Keywords: Modeling for control optimization, Disturbance rejection, Tracking
Abstract: This paper benchmarks a centralized control system based on model predictive control for the operation of the heat integrated distillation column (HIDiC) against a fully decentralized control system using the most complete column model currently available in the literature. The centralized control system outperforms the decentralized system, because it handles the interactions in the HIDiC process better. The integral absolute error (IAE) is reduced by a factor of 2 and a factor of 4 for control of the top and bottoms compositions, respectively.

Keywords: Modeling for control optimization, Evolutionary algorithms, Nonlinear predictive control
Abstract: This paper presents the use a neural network and a micro genetic algorithm to optimize future set-points in existing hydronic floor heating systems for improved energy efficiency. The neural network can be trained to predict the impact of changes in set-points on future room temperatures. Additionally, weather disturbances such as solar heat gain can be anticipated and compensated for, while taking into account the slow dynamics of the floor. Together with a genetic algorithm, they provide a way to search for optimal future set-point sequences, when convexity and continuity in the solution space is not guaranteed. Evaluation of the performance of multiple neural networks is performed, using different levels of information, and optimization results are presented on a detailed house simulation model.

Keywords: Modeling for control optimization, Large scale optimization problems, Control design for hybrid systems
Abstract: This paper proposes a new control method that can save the energy consumption of multi-case supermarket refrigerators by explicitly taking into account their interconnected and switched system dynamics. Its novelty is a bilevel combinatorial optimization formulation to generate ON/OFF control actions for expansion valves and compressors. The inner optimization module keeps display case temperatures in a desirable range and the outer optimization module minimizes energy consumption. In addition to its energy-saving capability, the proposed controller significantly reduces the frequency of compressor switchings by employing a conservative compressor control strategy. However, solving this bilevel optimization problem associated with interconnected and switched systems is a computationally challenging task. To solve the problem in near real time, we propose two approximation algorithms that can solve both the inner and outer optimization problems at once. The first algorithm uses a linear approximation, and the second is based on the submodular structure of the optimization problem. Both are (polynomial-time) scalable algorithms and generate near-optimal solutions with performance guarantees. Our work complements existing optimization-based control methods (e.g., MPC) for commercial refrigerators, as our algorithms can be adopted as a tool for solving combinatorial optimization problems arising in these methods.

Keywords: Modeling for control optimization, Sliding mode control, Power systems
Abstract: This paper presents the design of a high level Model Predictive Control (MPC) for efficient management and consumption of energy resources in microgrids locally controlled via Sliding Mode Control (SMC). The proposed MPC relies on a new model of the so-called Energy Management System (EMS), which takes into account the involved powers as new inputs. In the paper, the microgrid includes a Distributed Generation unit (DGu), based on a renewable energy source, and two Energy Storage units (ESus), working both in grid-connected and islanded operation mode and controlled by SMC. The MPC module generates the references of power for the energy storage systems, taking into account input and state constraints. The proposed approach is theoretically analyzed and the asymptotical stability of the controlled systems is proved. Simulation assessment confirms the efficacy of the proposal.

Keywords: Industrial applications of optimal control, Modeling for control optimization, Power systems
Abstract: Variable speed drives (VSDs) are AC/DC/AC power converters that drive electric machines at variable frequency. In a VSD the electric energy is first rectified to DC, then stored in a DC-link, and finally inverted back to the desired AC signal. The energy stored in the DC-link can be kept within tight bounds when the rectifier and the inverter coordinate their actions. This is achieved by utilizing model predictive control (MPC), which translates the control task into a sequence of optimization programs. In this paper we show how to utilize the structural properties of the underlying system to solve these optimization programs efficiently. We decompose the VSD into the rectifier, the DC-link and the inverter, and we use the alternating direction method of multipliers (ADMM) to exploit this decomposition. We show that our proposed method behaves favorably when compared to an interior point method, or a conventional ADMM approach.

Keywords: Stability of nonlinear systems, Anti-windup, Robustness analysis
Abstract: This paper presents improved versions of the Circle and Popov Criteria for Lure systems in which the nonlinear element is both sector and magnitude bounded. The main idea is to use the fact that if the nonlinearity is magnitude bounded and the linear system is asymptotically stable, then its state will be ultimately bounded. When the state enters this set of ultimate boundedness, it will satisfy a narrower sector condition which can then be used to prove stability in a wider set of cases than the standard Circle and Popov Criteria. The results are illustrated with some numerical examples.

Keywords: Stability of nonlinear systems, Lyapunov methods, Application of nonlinear analysis and design
Abstract: In this paper, an in-depth analysis of a nonlinear matricial fixed-point iteration and its convergence properties is provided. Remarkably, the analyzed iteration can be regarded as a "frequency-sampled'' version of a thoroughly investigated and very efficient fixed-point iteration for Kullback-Leibler approximation of spectral densities, proposed in [Pavon and Ferrante, 2006]. A proof of global convergence to a prescribed set of fixed points of the latter iteration seems to be elusive, though conjectured and corroborated by an extensive campaign of numerical simulations. The present work represents a first step towards the solution of this conjecture.

Keywords: Stability of nonlinear systems, Lyapunov methods, Descriptor systems
Abstract: The problem of the stability analysis for nonlinear differential-algebraic systems is addressed using tools from classical control theory. Exploiting Lyapunov Direct Method we provide linear matrix inequalities to establish stability properties of this class of systems. In addition, interpreting the differential-algebraic system as the feedback interconnection of a dynamical system and an algebraic system, a sufficient stability condition has been derived using the small-gain theorem. The proposed techniques are illustrated by means of simple examples.

Keywords: Stability of nonlinear systems, Lyapunov methods, Input-to-State Stability
Abstract: This paper raises the issue of undesirable sublevel sets generated by Lyapunov functions for interconnection of integral input-to-state stable (iISS) systems. Sublevel sets are important information of forward invariant sets describing behavior of systems. This paper demonstrates for the previously available Lyapunov function that in the case of small stability margins, sublevel sets are compressed in one direction and stretched in the other direction extremely when a component system is not input-to-state stable (ISS). This paper also shows conservativeness of such sublevel sets by proposing a new Lyapunov function producing much better sublevel sets. The developments reveal practical issues to which we need to attend carefully when a component system is not ISS.

Keywords: Input-to-State Stability, Lyapunov methods, Control of interconnected systems
Abstract: This paper peruses path-wise bounds, integral input-to-state stability and integral noise-to-state stability for stochastic nonlinear systems and proposes their Lyapunov-type characterizations. The characterizations are utilized to develop small-gain criteria to verify stability of interconnected systems. In contrast to preceding results, the developments allow stochastic noise to be active globally in the state space. The obtained criteria are made parallel to deterministic ones by resolving fundamental issues arising from stochastic noises.

Keywords: Stability of nonlinear systems, Positive systems, Networked systems
Abstract: We consider a generalized notion of differential positivity of a dynamical system with respect to cone fields generated by cones of rank kgeq 2. The property refers to the contraction of such cone fields by the linearization of the flow along trajectories. It provides the basis for a generalization of differential Perron-Frobenius theory, whereby the Perron-Frobenius vector field which shapes the one-dimensional attractors of a differentially positive system is replaced by a distribution of rank k that results in k-dimensional integral submanifold attractors instead. We further develop the theory in the context of invariant cone fields and invariant differential positivity on Lie groups and illustrate the key ideas with an extended example involving consensus on the space of rotation matrices SO(3).

Keywords: Time-varying systems, Linear systems
Abstract: In this paper we investigate properties of the Perron exponents of diagonal discrete linear time-varying systems. We give necessary and sufficient conditions for a function f to be the Perron function of the considered systems.

Keywords: Stability of nonlinear systems, Model validation, Distributed nonlinear control
Abstract: The stability in the sense of Lyapunov turned to be a most important property for equilibria and global trajectories of the dynamical systems. The so-called Stability Postulate of N. G. v{C}etaev states that only those trajectories and equilibria which are at least stable in the sense of Lyapunov are observable and measurable. On the other hand any mathematical model of some real (physical) process requires validation in order to be self consistent as a mathematical object, also to fit to data obtained from experiments (at least basically). Combining standard validation criteria for self consistency (existence, uniqueness, data dependence) with the Stability Postulate, also with other requirements will lead to the so-called textit{augmented model validation} for self consistency i.e. as a mathematical object. Since these new concepts (like the Stability Postulate) define a {em methodology} they have to be checked on applications (as v{C}etaev did). Therefore, there will be considered a case of energy co-generation described by conservation laws.

Keywords: Lyapunov methods, Stability of nonlinear systems, Power systems
Abstract: The problems of unconstrained optimization and establishing asymptotic stability have much in common. Understanding the analogy between these two sheds light on their interconnection and may lead to a number of new results. For instance, in this paper, we provide estimates of the rate of convergence when analyzing asymptotic stability of differential equations, rather than just ascertain the very fact of stability. Also, standard methods for the design of Lyapunov functions (e.g., those having the meaning of the full energy of the system) turn out to be unsatisfactory from this point of view and have to be modified. These claims are exemplified in the paper by considering the heavy-ball method for function minimization ``in parallel'' with the problem of asymptotic stability for the synchronous motor equation.

Keywords: Time-varying systems, Linear systems
Abstract: In this paper we consider the influence of parametric perturbations on the maximal Lyapunov exponent of the discrete time-varying system. The main result states that the exact upper movability boundaries of the greatest Lyapunov exponent under arbitrary small perturbations is the central exponent.

Keywords: Lyapunov methods, Asymptotic stabilization, Stability of nonlinear systems
Abstract: Stability of control systems is one of the central subjects in control theory. The classical asymptotic stability theorem states that the norm of the residual between the state trajectory and the equilibrium is zero in the limit. Unfortunately, it does not in general allow computing a rate of convergence, whereas proving exponential stability is notoriously complicated. This work proposes to revisit the asymptotic stability theory with the aim of computing convergence rates using constructive analysis which is a mathematical tool that realizes equivalence between certain theorems and computational algorithms. The overall goal of the current study matches with the trend for introducing formal verification tools into control theory. Besides existing approaches, constructive analysis, suggested within this work, can also be considered for formal verification of control systems. A computational example is provided that demonstrates extraction of a convergence certificate for a dynamical system

Keywords: Stability of nonlinear systems, Lyapunov methods, Application of nonlinear analysis and design
Abstract: This paper deals with asymptotic stability criteria for equilibrium points of nonlinear autonomous systems formulated in terms of compact invariant sets and positively invariant sets. To verify these criteria the functional method of compact invariant sets localization is used. The obtained results can be applied to show the asymptotic stability property in critical cases and to construct a Lyapunov function if the equilibrium point is (globally) asymptotically stable. The theoretical results are illustrated by examples.

Keywords: Information processing and decision support
Abstract: Urban development is a critical issue that many cities are facing, due to the demography growth which results from the economic attractiveness of the urban centers. Based on common standards such as the Urban Development Plans, some projects for transportation systems renewal are progressively launched. In order to allow social cohesion, especially by providing travelers with services which may allow to better organize the transport, it is necessary to structure the transportation system according to sustainability requirements. This paper examines an integrated approach for assessing the sustainability of the current transportation system design, based on a policy making problem, aiming at providing decision makers with a framework allowing them to choose the most eco-responsible policy amongst many alternatives. Since the sustainability indicators may conflict each other, in order to better take into account the requirements of the whole transportation system in its design phase, a system-based approach has been adopted to characterize the complex structure of these indicators. A general methodology for their elicitation is proposed, using a process-object methodology and based on surveys from recent research on sustainable transportation, along with eco-design principles, in order to take into account urban transport priorities, sustainability challenges and the analysis of the whole lifecycle of the transport infrastructure and equipment. To validate this proposal, a multi-criteria decision method, allowing subjectivity, uncertainty, incomplete judgments and group consensus is then performed, based on a case study which shows the flexibility of fuzzy analytical hierarchy process for such assessment.

Keywords: autonomic transport systems, Cooperative navigation, Multi-vehicle systems
Abstract: Latest research in the field of fully autonomous driving led to a new control approach based on decentralized control algorithms for macroscopic traffic scenarios. This control approach balances the traffic load (density) within a road network segment of limited area to maximize the vehicle throughput and to avoid traffic jams. However, it is necessary to divide the road network into multiple individual segments of limited area in an appropriate way. Due to the lack of a methodology to locate such locations for limited areas within a road network, this work presents an adopted technique that solves this problem by modelling the road network as spatial network and by using graph centrality indices. The presented method was implemented into a software framework and validated by simulation.

Keywords: Modeling and simulation of transportation systems, Automatic control, optimization, real-time operations in transportation
Abstract: In a recent paper (R. U. Chavan et al., 2016), the authors proposed a dynamic model of traffic behaviour on (Indian) roads, where lane discipline is not maintained even when the roads are wide and multiple vehicles can travel abreast. The primary hypothesis in this model was that each driver is influenced by an assortment of neighbouring cars and not only by the vehicle immediately in front. The proposed equations claim to be a model for driver/vehicle movement on such roads and hence should be able to predict actual motion of real vehicles. In this paper we experimentally verify this claim, after suitable modification of the theory to make it applicable for heterogeneous traffic. Videos of normal traffic on a sample road in Mumbai city, India, is recorded from the top of an adjacent high-rise building. Detailed motion information of groups of cars is extracted through novel image processing techniques. The proposed model is initialized with the extracted data and the computed trajectories are compared with the actual ones calculated from the images. It is verified that the proposed model can accurately predict complex maneuvers, such as overtaking, sideways movements (lane-changing) and avoiding collisions with slower moving vehicles.

Keywords: Automatic control, optimization, real-time operations in transportation, Modeling and simulation of transportation systems, Intelligent transportation systems
Abstract: Bus operations, due to their unstable nature, are inefficient when left uncontrolled with respect to retaining headways. Irregularities such as bus bunching lead to loss of time and decrease bus service quality. Development of bus transport system management schemes to avoid bus bunching and improve performance are of high importance, and has thus been the focus of many works in the public transport systems literature. Motivated by the importance of developing bus control strategies for improving performance, and specifically by the lack of a detailed but computationally efficient mathematical model describing bus transport system dynamics in the literature (which can facilitate model-based control design), we propose a mixed logical dynamical model of a single loop bus transport system, which involves both continuous (e.g., bus positions) and binary (e.g., the state of a bus regarding whether it is holding at a certain stop or not) states. Furthermore, we develop a hybrid model predictive control scheme with actuation via bus speeds, which can regularize headways and improve bus service quality. Performance of the predictive controller is evaluated via simulation experiments using the proposed model, where the passenger demands and maximum bus speeds are extracted from data collected from the bus network of the city of Fribourg. Results indicate the potential of the proposed controller in avoiding bus bunching and decreasing passenger travel times.

Keywords: Simulation, Modeling and simulation of transportation systems, Hybrid and alternative drive vehicles
Abstract: Creating a driving cycle (DC) for the design and validation of new vehicles is an important step that will influence the efficiency, functionality and performance of the final systems. In this work, a DC synthesis method is introduced, based on multi-dimensional Markov Chain, where both the velocity and road slope are investigated. Particularly, improvements on the DC synthesis method are proposed, to reach a more realistic slope profile and more accurate fuel consumption and CO2 emission estimates. The effects of using synthesized DCs on fuel consumption are investigated considering three different vehicle models: conventional ICE, and full hybrid and mild hybrid electric vehicles. Results show that short but representative synthetic DCs will results in more realistic fuel consumption estimates (e.g. in the 5%-10% range) and in much faster simulations. Using the results of this proposed method also eliminates the need to use very simplified DCs, as the New European Driving Cycle(NEDC), or long, measured DCs.

Keywords: Process control, Disturbance rejection (linear case), Control problems under conflict and/or uncertainties
Abstract: A computer-aided control system design tool is presented. This tool is able to take advantage of a database of Pareto optimal PID controllers. The idea is to give to the control engineer an useful tool to close the gap between the optimization procedure and the final selection of the parameters. The input to the tool are the allowed degradation of the considered cost functions, the desired level of robustness and the information of the plant, in the form of second order plus time delay model or a set of input-output data. The tool is written as a graphical user interface in MATLAB and freely available to anyone.

Keywords: Process control, Linear multivariable systems, Parametric optimization
Abstract: The controller tuning affects the control performance as much as the input/output (I/O) pairing. Thus, an optimal tuning should be sought simultaneously with the best I/O pairing, and not after the pairing has been defined. An optimal multi-objective technique for integrated control structure selection and tuning is proposed and applied to industrial benchmarks. The technique integrates the tasks of I/O pairing and controller tuning, and supports any multi-objective specification. It allows the direct employment of complex specifications of control problems, solving the I/O pairing problem simultaneously with the tun-ing problem. The technique is applied to two industrial benchmarks, a 3x7 heavy oil fractionator (HOF) and a 6x7 fluid catalytic cracking (FCC) units. The examples demonstrate the complete control project, including the PID I/O pairings, controller tuning, system identification and MPC implementation.

Keywords: Process control, Linear systems
Abstract: This paper presents new simple tuning rules for the gain in feedforward compensators. When the ideal feedforward controller is not possible to implement, a negative effect is introduced in the closed-loop response. So, the closed-loop transfer function from the disturbance to the error is analyzed and tuning rules for the feedforward gain are proposed. Two feedforward structures are used, a lead-lag compensator and a static controller. First, the feedforward gain is tuned to reduce the overshoot in the response for both compensator structures. Afterwards, a second tuning rule for the feedforward gain is derived to minimize the integrated absolute error. Finally, the different tuning rules are evaluated through simulations and compared with other existing solutions in the literature.

Keywords: Structural properties, Industrial applications of optimal control, Fault-tolerant
Abstract: In this paper, with the help of the Youla parameterization, the realizations of feedback control systems are discussed which results in a preferable and more convenient way to realize plug-and-play (PnP) control without modifying pre-designed control systems. Furthermore, based on the equivalence of different realizations of the Youla parameterization, a link between the standard feedback and the observer-based state feedback control system is given so that the well developed observer-based control techniques, like LQG/H2 control etc., can be achieved in the standard feedback control system via PnP control design. The effectiveness of the proposed PnP design schemes is verified using a direct current (DC) motor benchmark system.

Keywords: Process control, Fractional systems
Abstract: In order to improve the performance of control systems, a fractional order model predictive control (FMPC) algorithm using extended non-minimal state space (ENMSS) model is presented in this paper. For this propose, the fractional order model that describes the characteristics of practical processes more accurate than integer order model and the model predictive control (MPC) method based on ENMSS model that includes the state variable and output tracking error are considered. In this paper, the Grünwald-Letnikov (GL) definition is used to discretize the fractional order model and the fractional order cost function. This algorithm inherits the advantages of integer order extended non-minimal state space model predictive control (ENMSSMPC) with more adjustable parameters and better disturbance rejection, such that the controller tuning is more flexible. By comparing with the integer order ENMSSMPC, the results of the temperature control of an industrial heating furnace indicate the performance improvement of the proposed method.

Keywords: Systems with time-delays, Process control, Robust time-delay systems
Abstract: In this paper, a further enhanced active disturbance rejection control method is proposed for time-delay systems, which can be generally applied for open-loop stable, integrating and unstable processes. The plant model is adopted to design an extended state observer (ESO) such that both the disturbance and the unknown plant dynamics could be estimated. Then a prediction filter is designed to estimate the delay-free output response for control design, while satisfying the asymptotic stability constraints. A notable merit is that there is a single tuning parameter in the proposed ESO or controllers, which can be monotonically tuned to achieve a good trade-off between the control performance and robustness. The robust stability constraint of the closed-loop system is derived in terms of the linear matrix inequality and the Wirtinger inequality. An illustrative example is given to demonstrate the effectiveness of the proposed method.

Keywords: Linear systems, Linear parameter-varying systems, Robustness analysis
Abstract: In robust control problems it is often convenient to consider maps between controller sets that are defined by Mobius transformations. Moreover, these loop-transformations are also intimately related to different factorizations, that simplify the structure of the problem.

Starting from a fundamental observation that relates internal stability of the control loops to mere stability of a specific LFT, the paper provides an exhaustive answer to the question under which conditions the internal stability of a control loop is preserved by performing a loop-transformation. As a main result it is shown that Mobius transformations defined by unimodular matrices preserves the internal stability of the loop and an explicit formula is also given that relates the two loops. This result is formulated in a general context that includes LTV or LPV systems as well.

The paper also provides an overview on the different transformation techniques, as Mobius transformations, LFTs, different generalized chain scattering (CSD) transforms, and their interrelations. This knowledge gives a solid basis for those approaches that use an input-output framework in combination with the IQC analysis and synthesis techniques in the solution of linear parameter varying (LPV) design problems.

Keywords: Linear parameter-varying systems, Stability of hybrid systems, Robust control
Abstract: Linear Parameter-Varying (LPV) systems with piecewise differentiable parameters is a class of LPV systems for which no proper analysis conditions have been obtained so far. To fill this gap, we propose an approach based on the theory of hybrid systems. The underlying idea is to reformulate the considered LPV system as an equivalent hybrid system that will incorporate, through a suitable state augmentation, information on both the dynamics of the state of the system and the considered class of parameter trajectories. Then, using a result pertaining on the stability of hybrid systems, two stability conditions are established and shown to naturally generalize and unify the well-known quadratic and robust stability criteria together. The obtained conditions being infinite-dimensional, a relaxation approach based on sum of squares programming is used in order to obtain tractable finite-dimensional conditions. The approach is finally illustrated on two examples from the literature.

Keywords: Parameter-varying systems, Robust control, Constrained control
Abstract: Many works in literature are based on the idea that a nonlinear system with sector-bounded nonlinearities can be expressed as a quasi-LPV system. The convex difference inclusion (CDI) modelling framework proposed by M. Fiacchini and coworkers in several of their works generalises the modelling procedure and proposes robust controllers for them. In fact, their work can be further generalised to a quasi-convex framework with minor modifications to the proposed algorithms. The generalisation allows for less conservative modelling and, subsequently, less conservative estimates of lambda-contractive and invariant sets for such classes of models keeping reasonable computational tractability, at least in low-dimensional cases.

Keywords: Output regulation, Digital implementation, Robust control
Abstract: In this paper, we study the event-triggered global robust output regulation problem for a class of nonlinear systems in output feedback form with unity relative degree. We first convert the problem into the event-triggered global robust stabilization problem of a well defined augmented system by the internal model approach. Then, we solve the stabilization problem by an output-based event-triggered control law together with an output-based event-triggered mechanism. Finally, the theoretical result is applied to the Lorenz systems.

Keywords: Continuous time system estimation, Linear parametrically varying (LPV) methodologies
Abstract: This paper presents a new method for guaranteed and robust estimation of sideslip angle and lateral tire forces with consideration of cornering stiffness variations resulting from changes in tire/road and driving conditions. An interval LPV observer with both measurable and unmeasurable time-varying parameters is proposed. The longitudinal velocity is treated as the online measured time-varying parameter and the cornering stiffness at front and rear tires are assumed to be unknown but bounded with a priori known bounds. The obtained results are no more punctual values but a set of acceptable values. The simulation is based on experimental data in order to prove the effectiveness of the proposed observers.

Keywords: Time-varying systems, Robust estimation
Abstract: This paper is concerned with robust output estimator synthesis for discrete-time linear periodically time-varying (LPTV) systems with uncertainties. To evaluate robustness of estimation, we exploit the separator-type robust stability theorem under the cycling-based treatment of LPTV systems; we call such an approach for robustness analysis cycling-based LPTV scaling. Then, we derive a linear matrix inequality condition for robust estimator synthesis. A noteworthy property of our cycling-based synthesis approach is that we can predetermine the estimator period in the synthesis regardless of the system period, which is difficult to achieve in the case with the lifting-based treatment of LPTV systems.

Keywords: Mechatronic systems, Smart Structures, Design methodologies
Abstract: Today's engineering work flow of resources, e.g. units of automotive assembly lines or robotic cells in the body shop, shows up some gaps in provision of information in different engineering disciplines like mechanical-, electrical- or software engineering. The common issue is addressed by the kind of description of the technical and functional needs that mostly production planners are using in the planning phase. This article focuses the gap of describing required resources and introduces a method to auto-generate formalized object-related requirements by using a formalized process-description language. The general functionality of the method is presented by two use cases. Further, a way to exchange and provide this auto-generated engineering data in the engineering work flow is introduced by a suggested implementation in ReqIF. Towards seamless engineering data provision a call for integration of the ReqIF in AutomationML is given.

Keywords: Mechatronic systems, Motion Control Systems, Human Mechatronics
Abstract: In this paper, a model-based tracking control is proposed for a mechanism dedicated to accurately reproduce the breathing-induced motion of a human lung tumour. A lung tumour mimic model should perform the same smooth motion as a real one in a human body during inhalation and exhalation. In former work, a 3-dimensional mechanism equipped with three pneumatically driven axes has been developed and built up for this purpose. The discrete-time control structure consists of cascaded control loops: In the fast inner loops, the chambers pressures of the pneumatic cylinders are controlled, whereas the outer loops are related to the position control of the cylinders. Furthermore, iterative learning controllers are employed to compensate model uncertainties and lumped disturbance forces. The proposed overall control structure has been implemented and successfully validated on the innovative test rig.

Keywords: Modeling, Mobile robots
Abstract: In this article, we propose a general symbolic dynamic modelling framework devoted to Mobile Multibody Systems subject to hard persistent contacts. In particular, all rigid planar and spatial wheeled vehicles belong to this class of systems. To illustrate the approach we apply it to a realistic model of the three dimensional bicycle. Though being a familiar object for everybody, deriving the fully nonlinear dynamics of this system in a closed symbolic form is far from being trivial. Using a Newton-Euler algorithm coupled to a projective approach based on an explicit model of the contacts, the approach is successfully applied to the simulation of a free bicycle. It shows how the passive asymptotic stabilisation of the bicycle can be naturally ensured when it is thrown with sufficient initial velocities.

Keywords: Design methodologies, Application of mechatronic principles, Mechatronics for Mobility Systems
Abstract: Fast and precise actuation plays a key role to reach challenging drivability targets of an automatic transmission. Electro-hydraulic actuation systems are mainly used to fulfill the demanding requirements in state-of-the-art applications. Additionally to control tasks, the electro-hydraulic system is responsible for the cooling and lubrication of gears, clutches and other parts of the transmission. The focus of this article is to optimize a hydraulic layout design, satisfying various demands from lubrication, cooling, transmission efficiency as well as production costs. The presented approach analyses the different requirements in detail and derives corresponding rules for possible hydraulic layouts. A standard automotive test cycle is used to illustrate and quantify the design considerations of the different topologies. Additionally, worst-cases scenarios are considered to take into account cases that are not covered explicitly in the provided test cycle. The system costs and the average power consumption of the hydraulic layout are shown to be the two essential optimization criteria finally left for the design decision. With respect to essential optimal criteria a corresponding multi-objective optimization is performed and the optimal solutions are discussed.

Keywords: Modeling, Mechatronic systems, Design methodologies
Abstract: Process simulations are useful test-beds for experiments and optimizations along the entire industrial plant life-cycle. Shifting testing and tuning of industrial plants and their automation systems from the real world to simulated environments is a part of a virtualization, which is one of the key movements in emerging areas of Industry 4.0 and factories of the future. Although simulations bring a large variety of benefits, they suffer from a time-consuming and error-prone design phase, which limits their use in industrial practice. This paper proposes a new design method called AML2SIM, which transforms the real plant description represented in AutomationML (AML) and generates a dynamic simulation model (SIM). The proposed method significantly improves the engineering and re-design of simulation models in terms of saving time and effort of experts as the models can be easily re-generated based on a given AutomationML plant model. Simulations are assembled from simulation blocks that are shared among various projects in simulation libraries, hence the method contributes to reuse of simulation artifacts.

Keywords: Mechatronic systems, Motion Control Systems
Abstract: Planning and stabilizing induced oscillations for underactuated mechanical systems are challenging tasks. Available analytical solutions are primary linked to formats of representation of feasible trajectories and can give a rather limited perception of a variety of possibilities for particular systems. The paper provides new insights to the tasks exploring the classical and popular robotic benchmark set-up. In particular, the case study illustrates the procedure for generating a periodic behavior of a pendulum on a cart, when the pendulum oscillates around the horizontal. Planning such a behavior requires novel arguments for establishing a presence of a forced cycle. Furthermore, if found, the orbital stabilization of the cycle requires an alternative set of transverse coordinates. Both assignments are successfully solved. The analytical contributions are discussed and supported by numerical simulations.

Keywords: Vibration control, Motion Control Systems, Microsystems: nano- and micro-technologies
Abstract: In the magnetic-head positioning system in hard disk drives (HDDs), it is hard to analyze the effect of mechanical resonances beyond the Nyquist frequency after the HDDs were assembled. However, unexpected variations of mechanical characteristics often happen in actual HDDs because HHDs are mass-produced products. To solve such a problem, this paper proposed the analysis method of the sensitivity characteristics including the intersampling oscillations for the magnetic-head positioning control system of HDDs. This method enables us to analyze the performance of the magnetic-head positioning control system beyond the Nyquist frequency by using measurable open-loop characteristics. To show the validity of the proposed method, this study conducted simulation analyses on the magnetic-head positioning control system. The simulation results show that proposed sensitivity characteristics are good approximated solutions.

Keywords: Micro and Nano Mechatronic Systems, Motion Control Systems
Abstract: In order to overcome the limiting trade-off between the imaging speed and scanning range of an atomic force microscope (AFM), this paper combines two piezoelectric actuators as a dual stage actuator (DSA) for a lateral motion (X axis) of the AFM probe with respect to the sample. As the first actuator, a piezoelectric tube actuator of the commercial AFM is utilized. Although the actuator realizes a relatively large actuation range, it has the first mechanical resonance at a low frequency of 2.5 kHz. In the case of high-speed imaging, this resonance impairs the imaging speed and quality. In order to overcome this, a piezoelectric shear actuator with the first resonance at 19 kHz is selected as the second actuator, combined in the commercial AFM. To generate the X-axis motion by synchronizing those two actuators, this paper proposes a feedforward control design for DSAs in the frequency domain, which takes into account the actuator dynamics. In the proposed approach, triangular raster scan is composed as a Fourier series by individually adjusting the complex Fourier coefficients for each actuator. The effectiveness of the DSA and its control is validated by experimental AFM imaging at a scan rate of 200 Hz, where the lowest frequency component is applied to the tube actuator and the other higher components of the scanning signal to the high-speed shear actuator.

Keywords: Mechatronic systems, Motion Control Systems
Abstract: Disturbance suppression in the transport system of tape drives is essential for achieving high volumetric densities in tape storage, as improved tension control will enable operation with thinner tape media. In addition, tension variations lead to dimensional changes in the cross-track direction of the tape that must be accounted for in the track width budget. Hence, better tension control enables a higher track density. Furthermore, fluctuations of the tape velocity and tension around the nominal values impact the performance of the data channels, and consequently also the achievable areal recording density. In a tape transport system, disturbances are mainly induced by reel eccentricities that lead to time-varying tension disturbances. In this paper, the tension disturbances are first characterized using a strain-gauge sensor included in one of the rollers that determine the tape path. Then, a second characterization method that does not rely on a strain-gauge sensor is introduced. The new method is based on an estimate of the tension variation signal, which is derived from the difference of head lateral position measurements obtained by reading servo patterns on two adjacent servo bands. A tension feedback system is proposed, which uses time-varying controllers that adapt their frequency characteristics depending on the longitudinal tape position. The closed-loop system is designed to enhance disturbance suppression at the reel rotation frequencies. Experimental results are presented to illustrate the performance of the proposed tape transport control system.

Keywords: Micro and Nano Mechatronic Systems, Modeling
Abstract: The Landauer’s Principle, proposed by Rolf Landauer in 1961, states that the logically irreversible operation of erasing a single bit of information requires atleast kbT ln 2 amount of energy, kb and T being Boltzmann’s constant and temperature respectively. However, Landauer’s bound holds only for erasure mechanisms that are perfect. In this article we investigate the effect of imperfections in erasure mechanisms. If the proportion of successful erasures is quantified by p, we show that the minimum energy needed to erase a bit of information is given by kbT[ln 2+p ln p+(1−p) ln(1−p)], also known as the Generalized Landauer bound. Furthermore, we provide a mechanism for realizing a memory bit by multiplexing an optical trap rapidly and propose a mechanism of erasure, for various success proportions p. Using our framework, we show using Monte Carlo simulations that heat dissipation lower than the Landauer’s bound is achievable by reducing p. Thus, we establish an independent method of beating Landauer’s bound by resorting to partially successful erasures.

Keywords: Motion Control Systems, Mechatronic systems, Micro and Nano Mechatronic Systems
Abstract: Inherent non-linearity of piezo electric transducers, used in atomic force microscopy limits the position accuracy. In order to improve linearity, the elongation can be estimated by charge measurements. To extend the frequency range to DC, strain gauges are added by means of sensor fusion. This paper addresses the challenge of choosing the filter parameters for a first order complimentary filter used for sensor fusion. After identifying stochastic and systematic errors of charge and strain gauge measurements, the optimal parameters of a first order complimentary filter is computed. Depending on the application different filter parameters are found for the same nano-positioning system, by minimizing either stochastic errors, systematic errors or a combination of both. By this method the positioning uncertainty of charge monitoring (234.1 nm) and strain gauge measurement (347.1 nm) is reduced to 140.6 nm for a commercial tube piezo.

Keywords: Water quality and quantity management, Optimal operation of water resources systems, Dynamics and control
Abstract: Due to severe mathematical modeling and calibration difficulties open-loop feedforward control is mainly employed today for wastewater denitrification, which is a key ecological issue. In order to improve the resulting poor performances a new model-free control setting and its corresponding ``intelligent'' controller are introduced. The pitfall of regulating two output variables via a single input variable is overcome by introducing also an open-loop knowledge-based control deduced from the plant behavior. Several convincing computer simulations are presented and discussed.

Keywords: Uncertainty in water resource system control/management, Optimal operation of water resources systems, Natural and environmental systems
Abstract: Water level regulation of irrigation canals represents a major challenge for control systems design. Those systems exhibit large dynamic variation in their operating conditions. To overcome this fact, robust controllers should be applied. The sliding mode control paradigm reveals this ability which make it a suitable candidate to be incorporated in the irrigation canal control loop. Moreover, its exibility can be further potentiated by extending the ordinary formulation by adding fractional-order integro-differential operations. In this work, fractional-order sliding mode control is applied to the above mentioned problem. This application represents a novelty and, according to the obtained simulation results, leads to an accurate and proper performance when compared to its integer-order counterpart and to a fractional proportional-integrative controller, recently proposed for this problem.

Keywords: Game theory for natural resources, Real time control of environmental systems, Climate change impact and adaptation measures
Abstract: In this paper, we study the evolution of global cooperation through proposing a multi-level threshold public goods game model, and introducing an insurance compensation mechanism to probe the risk control. We find that high risk and high threshold are in favor of global cooperation. Furthermore, the introduction of insurance compensation remarkably promotes the emergency of global cooperative behaviors. On the other hand, the fixation time of global cooperation is sharply shortened after introducing insurance compensation mechanism. Besides, global cooperation is strengthened with the increase of imitation intensities.

Keywords: Natural resources management, Game theory for natural resources, Modeling and identification of environmental systems
Abstract: In this paper we consider a networked system of natural-resource consumption, where the agents are governed by a recently reported model of consumer psychology. Dynamics of the consumption for each agent are influenced by the state of the resource and consumption of her neighbors. The process is parameterized by the psychological characteristics of each agent. This study extends the original model to incorporate the underlying network topology, and explores the effects of aggregation via densely-connected communities present in the network. The exercise yields new interpretations of the predictions made by the original model in context of the influence network. We present aggregation mechanisms first for certain canonical structures of the consuming population and later on for a class of non-canonically structured populations. In the end we present an approximate aggregation scheme for populations where only some inaccurate information of the consumer characteristics is available.

Keywords: Modeling and identification of environmental systems, Scheduling, coordination, optimization, Modelling and control under change
Abstract: Renewable sources of energy play a decisive role in the current energetic paradigm to mitigate climate changes associated with greenhouse gases emissions and problems of energy security. Biomass energy and in particular forest wood biomass supply chains have the potential to enhance these changes due to its several benefits such as ability to produce both bioenergy and bioproducts, generate energy on-demand, among others. However, this energy source has some drawbacks mainly associated with the involved costs. In this work, the use of a Model Predictive Control approach is proposed to plan, monitor and control the wood-biomass supply chain for energy production at a tactical level. With this methodology the biomass supply chain becomes more efficient ensuring the service quality in a more competitive way. In order to test and validate the proposed approach different simulation scenarios were considered that proved the efficiency of the proposed tool regarding the decisions definition and control.

Keywords: Model reduction and dynamic emulation, Kinetic modeling and control of biological systems, Dynamics and control
Abstract: In this study a nonlinear mathematical model of plasticity in the brain is reduced using the Proper Orthogonal Decomposition and Discrete Empirical Interpolation Method. Such methods are remarkably useful for connecting reduced small scale models via the inputs and outputs to form optimally performing large scale models. Novel results were obtained as mathematical model order reduction has not been applied in neuroscience without linearization of the mathematical model and never to the model presented here. The reduced order model consumes considerably less computational resources than the original while maintaining a low root mean square error between the original and reduced model.

Keywords: Control of renewable energy resources, Smart grids, Control system design
Abstract: A modified control strategy for enhanced operation for a single phase rooftop PV connected to a single phase utility grid is presented in this paper. The current control is modified such that the quadrature references produced are independent of the grid side harmonics, which aids in the optimal control performance, even in polluted grid conditions. The transformations for the quadrature components are achieved using an inverse park phase locked loop (PLL), which enhances the PV performance, especially in the single phase. To assist the controller actions in the most efficient way, a TS fuzzy control for the DC link voltage regulation is used. Thus an improved performance for the rooftop PV With the proposed control topology is observed over the conventional control. The efficacy of the control scheme is tested in the MATLAB/ SIMULINK environment.

Keywords: Modeling and simulation of power systems, Power systems stability, Control of renewable energy resources
Abstract: The topic of this work joins in a wide theme treating with the security and the reliability of the operating mode of complex electronic circuits. A study of the dynamical behavior of a stand-alone photovoltaic system under digital controls is presented. Numerical simulations are illustrated in the time domain and in the parameters space. The objective of this work is to operate the mathematical advances of bifurcations theory to predict and control the bifurcations phenomena in an isolated photovoltaic plant. To accomplish this aim, we have presented a new discrete time model of the photovoltaic power system. The advantage of this model is that can be handled analytically with the aim to design controller to harness any abnormal behavior that can occur. Without time delayed feedback control (TDFC), the system may present undesirable behaviors such as chaotic solutions. Using this control theory, it is shown that TDFC is able to stabilize the interesting periodic orbit for larger values of proportional gain.

Keywords: Control of renewable energy resources, Application of power electronics
Abstract: An uncertainty and disturbance estimator (UDE)-based robust power flow control for grid-tied DC/AC converters was reported in the literature to achieve accurate power delivery in the presence of various types of model uncertainties and external disturbances. In this paper, a bounded-voltage power flow control is proposed for grid-tied PV systems with the improvement of the existing UDE-based robust power flow control to provide AC voltage protection.With the bounded-voltage design, the output voltage of the DC/AC converter always stays within the given range, which avoids the integrator windup caused by the saturation unit with the inappropriate setting of reactive power reference. Both simulation and experimental results are provided to demonstrate the effectiveness the proposed strategies.

Keywords: Smart grids, Real time simulation and dispatching, Intelligent control of power systems
Abstract: Future society entails new paradigms in how the world will work; new ideas as Smart Grid, Smart Cities, Smart Homes, an interactions between them have been established and studied.With the inclusion of Information and Communication Technology (ICT) components into the low-voltage (LV) distribution grid, some measurement data from smart meters are available for control of the distribution networks with high penetration of photovoltaic systems (PV). This paper takes a local voltage-control strategy for smart LV distribution networks, by using a novel fuzzy based methodology using local information collected from smart meters as status information source of the grid. Comparison studies are presented for a smart home LV distribution system to validate the method, showing the robustness of proposed method compared with the traditional local approaches. To illustrate the applicability of the proposed method, a real-time digital simulator for smart distribution power grids with a the developed voltage-control system are used. The results show that the proposed method can simultaneously mitigate the PV reactive power injection, as well as minimize the voltage rise and power losses.

Keywords: Control of renewable energy resources, Intelligent control of power systems, Optimal operation and control of power systems
Abstract: Recently, wind-solar-battery hybrid power generation has become one of the most popular methods to tackle the grid integrating problem of wind and solar power. A novel ultra-short-term pre-plane power curve based smoothing control approach is proposed for grid-connected wind-solar-battery hybrid power system (WSBHPS). A pre-plan power curve based scheduling module, which takes the grid limitation of maximum powers fluctuation, maximizing wind and solar power utilization and reducing use of battery energy storage system(BESS) as objectives, is designed according to ultra-short-term prediction information of wind and solar power and state of charging (SOC) of BESS. A real-time power fluctuation compensation module is designed based on weighted moving average filtering algorithm to smooth power fluctuation in real time. The results of simulation experiments show that the proposed approach could not only reduce the use of BESS, but also has better smoothing effectiveness compared with traditional low filter based smoothing control approach.

Keywords: Control of renewable energy resources, Optimal operation and control of power systems, Smart grids
Abstract: This paper proposes a solution for the day-ahead planning and the control of real-time operation of a large utility scale grid-connected system composed by a photovoltaic plant (PV) integrated with a battery energy storage system (BESS). The day-head planning algorithm determines the optimal daily energy delivery profile based on a prediction of the PV power production. The objective is to maximize the power delivery, according to the request of specific profile shape constraints, which can be defined by the transmission system operator. The real-time operation algorithm dynamically regulates the BESS power exchange, in order to realize the planned power profile and satisfying operational and technical constraints. The proposed algorithms use chance-constrained stochastic optimization, which allows the day-ahead planning and the real-time operation to stochastically take into to account long-term and short-term PV power predictions, respectively. Simulations results show the effectiveness of the proposed solutions.

Keywords: Dynamics and control, Artificial pancreas or organs, Control of physiological and clinical variables
Abstract: A novel Model Predictive Control (MPC) strategy for an artificial pancreas to treat people with type 1 diabetes mellitus is proposed and tested in-silico. The proposed controller has been designed to handle a large spectrum of meal sizes more effectively than the authors' current strategy. Hyperglycemia due to small meals is treated more assertively, leading to increased time in euglycemia, whereas hyperglycemia due to large meals is treated more cautiously, resulting in a markedly reduced risk of controller-induced hypoglycemia. This is achieved by replacing the purely quadratic cost function employed within the MPC optimization by a mixed linear-quadratic cost function. This simple modification results in significant leeway to design a controller that responds more effectively and safely to the dietary habits of the AP user, while maintaining the quadratic program structure of the resulting optimization problem. The proposed MPC strategy's benefits are demonstrated by in-silico analysis using the Universities of Virginia/Padova US Food & Drug Administration accepted metabolic simulator.

Keywords: Artificial pancreas or organs, Clinical trial, Control of physiological and clinical variables
Abstract: The first clinical trials using an Artificial Pancreas (AP) in Latin America have been defined in 2 stages. The first stage was carried out in November 2016 with the UVA controller (developed by the Center for Diabetes Technology and already clinically tested), and the second will be performed during the first semester of 2017 with the ARG (Automatic Regulation of Glucose) algorithm (developed by ITBA, UNQ, and UNLP in Argentina). Both tests are based on the DiAs (Diabetes Assistant) from the UVA, and are performed in the HIBA on 5 patients with Type 1 Diabetes Mellitus (T1DM), for 36 hours. For the first stage, Open-Loop (OL) insulin boluses were applied before meals and patient's physical activity was included. On the other hand, for the second stage, patients will not be involved in physical activity, but no OL insulin boluses will be injected before meals. In this work, experimental results from the first stage with the UVA controller, and preliminary results with the ARG control algorithm tested on the UVA/Padova simulator are presented. Due to the final paper deadline, the experimental results from the second stage are not included here, but will be presented at the IFAC World Congress.

Keywords: Artificial pancreas or organs, Control of physiological and clinical variables, Chronic care and/or diabetes
Abstract: In the last decade, control algorithms designed for Artificial Pancreas (AP) systems were characterized by significant progresses. In particular, the Control-to-Range Model Predictive Control (MPC) showed its effectiveness and safety in several real life studies. Recent studies on model individualization and the enhanced quality of glucose sensors further improved the efficacy of MPC, thus allowing moving from a Control-to-Range to a Control-to-Target approach. In this study, an integral action in the MPC approach (IMPC) is proposed. This ensures beneficial effects in terms of regulation to the target in presence of disturbances such as delays, pump limitation and model uncertainties. The integral action is even more important when model individualization is performed since, during the identification phase, it allows to focus on the identification of the dynamical part of the model rather than to the static gain. The patient models considered in this contribution have been identified through a constrained optimization approach. A procedure for tuning the IMPC aggressiveness by considering both the glucose control performance and the integral of the error with respect to the target is described. Finally, in silico experiments are presented to assess the effectiveness of the proposed IMPC.

Keywords: Artificial pancreas or organs, Chronic care and/or diabetes, Control of physiological and clinical variables
Abstract: Sliding Mode Reference Conditioning (SMRC) has been recently proposed as a new technique to limit insulin-on-board in an artificial pancreas system. It is based on the glucose set point modulation by means of an outer control loop to avoid violation of imposed insulin-on-board limits. Clinical evaluation under a mixed meal challenge has demonstrated, in combination with a PD controller, a significant improvement in postprandial control as compared to insulin pump therapy. However, advantages of SMRC as compared to the widely used Insulin Feedback in PID-based artificial pancreas systems have not been thoroughly investigated. As well, SMRC offers many possibilities of criteria for the selection of insulin-on-board limits according to the expected role of the outer loop with respect to the main controller. In this paper, all these aspects are investigated through an in silico study in face of a challenging scenario with multiple sources of variability.

Keywords: Artificial pancreas or organs, Biomedical system modeling, simulation and visualization, Control of physiological and clinical variables
Abstract: Meals are most challenging in the regulation of blood glucose levels (BGL) in diabetes mellitus type 1, whether it is automated, semi-automated or manually controlled. The common subcutaneous (SC) route for glucose sensing and insulin administration suffers from large latencies. This paper investigates the impact of glucose sensing and insulin absorption dynamics on the achievable glucose regulation when insulin boluses are triggered by a meal detection system. In silico patients from the academic version of the UVa/Padova simulator are studied. The sub-models of glucose sensing and insulin absorption are adjusted to allow simulations with different time delays and time constants. Meals are detected with published methods based on threshold-checking of continuous glucose monitoring data. Slow glucose sensing dynamics delay the meal detection. Delayed meal detection can be compensated to some extent by exact knowledge about the insulin absorption. The combination of slow glucose sensing and slow insulin administration reduces the effect of insulin boluses on the postprandial BGL. The classical SC approach is, therefore, at high risk of large BGL excursions despite meal detection.

Keywords: Artificial pancreas or organs, Chronic care and/or diabetes, Biomedical system modeling, simulation and visualization
Abstract: Model predictive control (MPC) algorithms have been used often within artificial pancreas control systems both in-silico and in clinical studies. Increasingly complex models in the controller can more accurately predict the glycemic response, but they introduce increased computational complexity which can be challenging to implement especially within an embedded environment where computational resources are limited. Less complex models are also preferable in that they can be evaluated in silico against more complex plant models. There has not yet been an evaluation of how the complexity of models used within an MPC impacts performance within an artificial pancreas. A model within an artificial pancreas MPC algorithm should be as complex as necessary to accurately predict a glycemic response to meals, exercise, stress, and other disturbances, but not overly complex. In this paper, we evaluate four glucoregulatory models used within an MPC, starting with a 4-state model and increasing in complexity up to six states. We evaluate the complexity using an in-silico population derived from a more complex glucoregulatory model (9 state variables). We assess how complexity of the model impacts performance both in terms of standard control metrics such as settling time and overshoot as well as clinically relevant metrics such as percent time in euglycemia (glucose between 70 and 180 mg/dl), percent time in hypoglycemia (<70 mg/dl) and percent time in hyperglycemia (>180 mg/dl). We find that model complexity matters far less than how well the model parameters match the individual subjects. When the simplest model is used, but fit to an individual subject’s data, it performed comparably with more complex models. We selected a middle-complexity model and integrated it into our previously published exercise-enabled MPC model and evaluated it in a virtual patient population both with and without the exercise model present. We found that increasing complexity by modeling exercise is critical to help enable early insulin shut-off by the controller to avoid hypoglycemia.

Keywords: Data-based control, Energy systems
Abstract: This paper deals with the problem of steering a system at a certain percentage of the optimal cost, so as to keep a desired amount of reserve. This reserve can be used as a knob to counteract fast changes in the operating conditions of the system. In this paper, we consider the case where the system dynamics as well as the analytical expression of the cost function are unknown. We propose a modified version of extremum seeking control that, under certain assumptions, is able to keep a desired margin with respect to the estimated maximum. The theoretical properties of the presented scheme are analysed and the effectiveness of the approach is validated in simulation on a wind turbine example.

Keywords: Data-based control, Nonlinear predictive control, Adaptive control
Abstract: This paper presents stabilizing Model Predictive Controllers (MPC) in which prediction models are inferred from experimental data of the inputs and outputs of the plant. Using a nonparametric machine learning technique called LACKI, the estimated (possibly nonlinear) model function together with an estimation of Hölder constant is provided. Based on these, a number of predictive controllers with stability guaranteed by design are proposed. Firstly, the case when the prediction model is estimated off-line is considered and robust stability and recursive feasibility is ensured by using tightened constraints in the optimisation problem. This controller has been extended to the more interesting and complex case: the online learning of the model, where the new data collected from feedback is added to enhance the prediction model. An on-line learning MPC based on a double sequence of predictions is proposed.

Keywords: Data-based control, Regulation (linear case), Linear multivariable systems
Abstract: In this paper, we propose a novel, data-driven approach to external model-based regulation for uncertain plant and known exosystem models. At the core of the method lies a technique for least-square estimation of the gains of the plant model at the frequency of excitation, which is adopted for the construction of a hybrid external model of an equivalent disturbance acting at the plant input. Interestingly, in spite of residual errors on the estimates (arising from the use of finite estimation intervals), the reset mechanism employed in the hybrid external model ensures asymptotic regulation, instead of practical regulation. Furthermore, the method does not require a priori knowledge of the transfer matrix of the plant, and takes advantage of an external approach to robust regulation, where the ensuing stabilization problem may be simpler than the ones typically found in internal model-based design.

Keywords: Data-based control, Linear systems, Lyapunov methods
Abstract: Our contribution in this paper is twofold. In the first part, we study Lyapunov functions when a plant is interconnected with a dissipative stabilizing controller. In the second, we present results on data-driven approach to dissipative systems. In particular, we provide conditions under which an observed trajectory can be used to determine whether a system is dissipative with respect to a given supply rate. Our results are based on linear difference systems for which the use of quadratic difference forms play a central role for dissipativity and Lyapunov theory.

Keywords: Data-based control
Abstract: Knowledge of a dissipation inequality can disclose valuable system properties relevant for controller design. Therefore, we consider the problem of determining a dissipation inequality for an input-output system. In practice, yet, the core issue is that one would only know finitely many input-output samples while the input-output relationship would be undisclosed analytically. For such scenarios, we provide an approach for computing dissipation inequalities based upon knowledge of large amounts of input-output samples, as they arise in applications nowadays gathered under the term “big data”. Our approach will, under certain conditions, provide dissipation inequalities which remain satisfied for all input-output pairs that the system can produce, though only having been derived from finitely many of them.

Keywords: Data-based control, Modeling for control optimization
Abstract: This paper deals with data-driven predictive control for relative performance management in virtualized software system. The system dynamics are characterized in Hammerstein-Wiener structure to capture nonlinear and linear characteristics. The proposed control approach is the implementation of Subspace-based Predictive Control with the integration of nonlinear compensation. The compensator functions are inverse static input and output nonlinearity models from the Hammerstein-Wiener system identification. The subspace predictors are formulated from the linear model input and output of Wiener block. The experimental results from three scenarios of performance objectives show the reliability of Subspace-based Predictive Control to manage the virtualized software system.

Keywords: Control system design, Application of power electronics, Optimal operation and control of power systems
Abstract: This paper presents a new speed control method for the induction motor (IM) following the finite control set-model predictive control (FCS-MPC) strategy. It adopts the cascaded control scheme, which consists of an inner model predictive torque control (MPTC) loop and outer model predictive speed control (MPSC) loop using two individual cost functions. This control approach implements a maximum torque per ampere (MTPA) operation in a wide speed range, which includes flux-increased and flux-limited modes. The MPSC produces the required torque to drive the IM at the reference speed. This torque is taken as the input of the inner MPTC, which in turn generates the optimal finite set of control input voltage. The control signals of the two MPC are constrained with the maximum limits of the system. The state feedback is achieved with a standard Kalman Filter, which estimates the non-measured load torque. The proposed control system is implemented and validated in experimental environment. The behaviour of the control system is evaluated by applying reference and disturbance steps to the system in different operational modes.

Keywords: Application of power electronics, Modeling and simulation of power systems, Control system design
Abstract: The work here reported tackles the problem of controlling in sliding-mode (SM) a boost converter supplying a constant power load (CPL). A linear switching surface is proposed to overcome the intrinsic unstable behavior of the converter in both ON and OFF states, this resulting in a significant mitigation of the inrush current and a high degree of output voltage regulation. A detailed analysis showing the converter trajectories in the phase-plane and the conditions for the existence of sliding-mode is presented. The analytical predictions are in perfect agreement with PSIM and MATLAB simulations.

Keywords: Modeling and simulation of power systems, Control system design, Application of power electronics
Abstract: A generic and mathematic tool is adapted and used for pulse width modulation inverter modelling and control. The model is developed on the elementary switching cell and finally extended to some N-level topologies and three-phase inverters. Based on the generalized inverses, the solution set of pulse width modulation carrier based scheme is highlighted. The degree of freedom highlighted for the modulation control are linked to the architecture described. A specific example is illustrated and based on a H-bridge 3 level topology.

Keywords: Applications of FDI and FTC, Analysis of reliability and safety, Application of power electronics
Abstract: This paper proposes a fault detection method and a tolerance control in a single-phase cascaded H-bridge multilevel inverter (CHBMI). In case of open-fault, the body diode of the fault switch provides a freewheeling current path. However, in case of short-fault, the freewheeling current path cannot be described by disconnecting of fuse and the distortion of output current is different from that of open-fault. Therefore, it is possible to separately detect the type of fault. When the open-fault or short-fault occurs, the output phase voltage has to limit because the single-phase CHBMI unable to compensate from another phase voltage like three-phase systems. Therefore, the reference voltage has to reconfigure, and the tolerance control is operated depending on the different fault types. In the proposed detection method, it is possible to detect not only the fault cell number but the fault location of switch accurately, and the quality of output current can improve through the proposed tolerance control when both open-fault and short-fault occur. The effectiveness and performance of proposed fault detection and tolerance control method are verified by simulation results.

Keywords: Application of power electronics, Control system design, Power systems stability
Abstract: In this paper a new filter design for the Uncertainty and Disturbance Estimator (UDE) is proposed to reject periodical disturbances when a limited bandwidth is required for the control output. The motivation comes from several applications where the system actuator may introduce a bandwidth limitation, as a result of internal delays, or when the actuator itself is a limited bandwidth closed-loop system. When the traditional UDE approach is applied in these systems, the stability requirements impose a limitation over the effective bandwidth of the UDE filter and therefore disturbances cannot be fully rejected by the filter. In the case where the expected disturbance is periodical with a known fundamental frequency, the proposed UDE filter is designed as a chain of filters to match selected bands of the expected disturbance spectrum and fully reject them while maintaining the desired stability margins. A design example of a power inverter application is investigated and extensive simulation results are provided to verify the proposed UDE filter design.

Keywords: Analysis and control in deregulated power systems, Application of power electronics, Power systems stability
Abstract: The impedance-ratio criterion has been widely adopted to analyze the stability of cascaded power electronic systems. However, for different cascaded systems, the impedance ratio takes different forms. For cascaded systems with a voltage-controlled source, it is the ratio of the output impedance of the source converter to the input impedance of the load converter. For cascaded systems with a current-controlled source, it is the ratio of the input impedance of the load converter to the output impedance of the source converter. In this paper, a generic stability criterion in terms of the sum of the impedances of individual subsystems is proposed. A cascaded system with individually stable subsystems is stable if and only if the sum of the impedances of the subsystems does not encircle the origin clockwise or equivalently the impedance sum does not have right-half-plan (RHP) zeros. Real-time simulation results are presented to validate this generic stability criterion.

Keywords: Engine modelling and control, Automotive system identification and modelling, Automotive sensors and actuators
Abstract: Control is essential to meet future emission requirements in combustion engines. Accurate models are required to design a controller that achieves robust performance over a range of operating conditions. The aim of this paper is to develop a non-parametric and parametric identification procedure that is specifically tailored towards high performance diesel engine control, while minimizing measurement time. First, a non-parametric identification is proposed where the inputs are excited with multisines. A Local Rational Method (LRM) is employed to obtain multivariable Frequency Response Functions (FRFs) in a single experiment. Secondly, a parametric identification procedure uses the non-parametric estimates to obtain control-relevant parametric models. The identification procedure is demonstrated using a modern Heavy-Duty Diesel (HDD) engine providing highly accurate low order parametric models for a 2x2 plant using just 300s of measurement time at an engine operating point.

Keywords: Hybrid and alternative drive vehicles, Nonlinear and optimal automotive control, Engine modelling and control
Abstract: Fuel optimal lock-up transients for a heavy duty series hybrid electric vehicle are studied. A mean value engine model is used together with numerical optimal control to investigate the interplay between electric machine, gearbox and engine with its turbocharger dynamics in particular how they influence the manner and rate at which the engine should be controlled in order to reach a synchronized speed with the gear-box, enabling lock-up. This is studied both for prescribed gear-box speeds, simulating a mechanical transmission, and with gear-box speed an optimization variable, simulating a continuously variable transmission. The optimal engine transients and their duration are seen to be dictated by the stationary efficiency of the different drivetrain modes, showing that the ratio between the efficiencies of the electric and mechanical path dominates the dynamics and have a greater effect than the engine and turbocharger dynamics. In particular the transition between the modes is as fast as possible when the conventional powertrain is the most efficient and as slow as possible when the engine-generator set is more efficient. This points out that the stationary efficiency maps can be used in a central way for the control design of lock-up transients.

Keywords: Adaptive and robust control of automotive systems, Hybrid and alternative drive vehicles
Abstract: In this paper the problem of online-optimizing the steady-state efficiency of a hybrid single-cylinder diesel power unit is considered. The special characteristic of the proposed concept is using the time path of the crankshaft position during one combustion cycle as an optimization variable. The problem can be stated in terms of an optimal control problem with free terminal time, which is solved by applying the model-free optimization scheme extremum seeking control. It is shown that by using a parameterization of the reference input based on trigonometric basis functions the evolution of the performance index can be modeled as a discrete-time nonlinear and multivariable system with a non-constant sampling interval. To this system the discretetime variant of ES can be directly applied. An advantage of the proposed method is that no modeling of the thermodynamic processes is required. The robustness and accuracy of the concept is at first studied through simulations. Furthermore, experimental results are presented demonstrating the need for a model-free optimization and the beneficial property of the concept’s adaptation capability.

Keywords: Modeling, supervision, control and diagnosis of automotive systems, Nonlinear and optimal automotive control, Engine modelling and control
Abstract: Due to the increasing availability of natural gas, there is growing interest in using this fuel for transportation. Utilizing natural gas along with gasoline can provide a way to leverage the high knock resistance of natural gas while avoiding some of the ignitability challenges of this fuel. This paper leverages experimental data for a single cylinder engine to model power production on a mid-size sedan. Using this model, an optimal energy management strategy is explored. Several weighting strategies are considered including techniques which consider fuel availability, fuel cost, and carbon emissions. The effectiveness of these methods are considered over the UDDS, HWY, and US06 cycles. While there is little benefit to such a fuel blending algorithm at low loads, at high loads (such as those encountered in the US06 cycle) blending can provide up to a 7% improvement in efficiency.

Keywords: Modeling, supervision, control and diagnosis of automotive systems, Hybrid and alternative drive vehicles, System integration and supervision
Abstract: Pressure to reduce CO2 emissions is driving the automotive industry toward the electrification of powertrains. To support this trend Continental Automotive continues to develop components and advanced system control functionalities. To validate these new control functionalities, the existing Hardware In the Loop vehicle model was extended to include a model of the hybrid system. This paper describes the model requirements, the modelling methodology and the model validation process. Finally an insight is given into some typical use cases for this model during the verification & validation (V&V) phase.

Keywords: Event-based control, Optimal control of hybrid systems
Abstract: The paper studies the H2 optimal sampled-data control of linear time-invariant systems. The sampling pattern is assumed to be uniformly bounded but otherwise arbitrary and a priori unknown. The derived optimal solution is analytic, computationally simple, implementable, and transparent. Properties of the optimal controller also suggest novel event triggering mechanisms, which preserve stability and tolerant of measurement noise. Applying to the benchmark problem of (Cervin, 16), the proposed event generation mechanisms outperform several existing approaches.

Keywords: Event-based control, Quantized systems, Control under communication constraints
Abstract: This paper considers the problem of containability for a scalar linear unstable system where the communication from the sensor to the actuator is performed over a network with finite capacity. The possibilities of event-based sampling concepts in a setup with memoryless coding and decoding components acting together with a static controller are investigated. A robust controller is designed such that the finite communication control system employs an arbitrary, possibly vanishing, average data rate in a delay free setup while guaranteeing containability. The controller can be applied in the presence of delays as well, whereas the sampling mechanism needs to be adjusted. This leads to an increasing data rate and this increase is precisely quantified. Indications why the uncertainty in time rather than the pure delay causes the increasing data rate are given as well as considerations regarding the relation of transmitted bits and delay.

Keywords: Event-based control, Reachability analysis, verification and abstraction of hybrid systems, Stability and stabilization of hybrid systems
Abstract: In this work, we design the sampling policy in sampled-data systems. It is known that implementing such systems using variable sampling periods, instead of a constant period, is more efficient in terms of performance and resource utilization. Thus, after rewriting the system in the framework of impulsive linear systems, a self-triggered control strategy obtained using reachability analysis is proposed in order to define the sampling period as a function of the state.

Keywords: Control over networks, Event-based control
Abstract: Event-triggered control is a control strategy which allows the savings of communication resources in networked control systems. In this paper, we are interested in periodic event-triggering mechanisms in the sense that the triggering condition is only verified at predefined periodic sampling instants, which automatically ensures that Zeno behavior does not occur. We consider the case where both the output measurement and the control input are transmitted asynchronously using two independent triggering conditions. The developed result is dedicated to a class of nonlinear systems, where both the plant model and the feedback law can be described by polynomial functions. The overall problem is modeled and analyzed in the framework of time-delay systems, which allows to derive sum-of-squares (SOS) conditions to guarantee the global asymptotic stability in terms of the sampling period and the parameters of the triggering conditions. The approach is illustrated on a nonlinear numerical example.

Keywords: Event-based control, Control over networks, Control under communication constraints
Abstract: The paper presents an observer-based event-triggered control strategy for linear systems subject to input cone-bounded nonlinearities by using only available measurable variables. Sufficient conditions based on linear matrix inequalities are proposed to ensure the asymptotic stability of the closed loop and the avoidance of Zeno behavior in an emulation context. Based on these conditions, a convex optimization problem to compute the parameters of the event-trigger rule aiming at reducing the number of control updates is proposed. The approach is illustrated on a numerical example that considers the control of a linear system with a logarithmic input quantization constraint.

Keywords: Event-based control
Abstract: This paper studies the event-triggered control problem for systems subject to both dynamic uncertainties and external disturbances. To overcome infinitely fast sampling caused by the disturbance, a new event-triggering mechanism is proposed, which uses not only the measurable system state but also an estimate of the unmeasurable state and the external disturbance. The inter-sampling intervals can be proved to be lower bounded by a positive constant, which is independent on the magnitudes of the unmeasurable state and the external disturbance. With the proposed design, the closed-loop event-triggered system can be input-to-state stabilized with the external disturbance as the input. Refined tools of input-to-state stability (ISS) and the small-gain theorem are employed in solving the problem.

Keywords: Autonomous robotic systems, Guidance navigation and control, Multi sensor systems
Abstract: This paper presents the design and assessment of an USBL-aided navigation approach for Autonomous Underwater Vehicles (AUV). The system integrates an Ultra-Short Base Line (USBL) acoustic modem and positioning device in a two-parallel Extended Kalman Filter (EKF) navigation schema, which also includes the measurements provided by an Inertial Measurement Unit (IMU), a Doppler Velocity Log (DVL), a Visual Odometer (VO), a pressure sensor, and a Global Positioning System (GPS). In order to be integrated in the estimation filter, the precision of the USBL measurements is derived experimentally. Moreover, the accuracy of the system is evaluated using a ground truth (GT) trajectory produced by a visual Simultaneous Localization and Mapping (SLAM) approach. Experimental results are obtained from marine datasets gathered in the north coast of Mallorca with an AUV, model SPARUS II.

Keywords: Mobile robots, Multi sensor systems, Autonomous robotic systems
Abstract: In this paper and its companion paper (Ahmadi Barogh and Werner, 2017), the problem of source seeking with a group of agents in a distance-based formation is considered. Each agent is equipped with appropriate sensors to detect the distance between itself and its neighbors and to measure the strength of a field signal. The task is to find a maximum point of the scalar field in the area. Each agent estimates the gradient of the scalar field cooperatively and moves in the gradient direction, by maintaining the specified formation in movement. In this paper, a distributed controller for navigation of single integrator agents is proposed. We use a distance-based formation controller to maintain a predefined formation when moving with collision avoidance. The center of formation converges to the region near the source and agents do not need access to a common coordinate system. Conditions are provided for the asymptotic stability of the system and for the formation center to converge a bounded region near the source. Simulation results are presented to illustrate the effectiveness of the proposed approach.

Keywords: Mobile robots, Multi sensor systems, Autonomous robotic systems
Abstract: In this paper and its companion paper (Ahmadi Barogh and Werner, 2017), the problem of source seeking with a group of agents in a distance-based formation is considered. Agents are equipped with a suitable sensor set to measure the distances to other agent and the strength of a field signal. The main objective of source seeking is to locate the maximum value of a scalar field in space. Each agent cooperatively estimates the gradient of the scalar field with respect to its local coordinate system and moves in the gradient direction, by maintaining the predefined formation. In this paper, a distributed controller for navigation of non-holonomic agents based on a dynamic model is proposed. The formation strategy used in this paper is a distance-based method to maintain a predefined formation during movement with collision avoidance. In a distance-based formation, global position information for agents is not required. Conditions are proposed for the asymptotic stability of the whole system and for the formation center to converge to the source. Simulation results are presented to show the effectiveness of the proposed control laws.

Keywords: Networked robotic system modeling and control, Flying robots, Robots manipulators
Abstract: In this paper, we develop a formation control law with collision avoidance for multiple quadrotor-manipulator systems that each quadrotor is equipped with a robotic manipulator. Firstly, the kinematic and dynamic models of a quadrotor with multi-DOF robotic manipulator are built together using Euler-Lagrange (EL) equations. Based on the aggregated dynamic model, we propose a control scheme consisting of position controller, attitude controller and manipulator controller, respectively. The desired formation is achieved by the proposed position controller and attitude controller, while the collision avoidance is guaranteed by an artificial potential function (APF) method. The robotic manipulators are able to perform cooperative missions by the proposed manipulator controller. The overall stability of the closed-loop system is proven by a Lyapunov method and Matrosov’s theorem. In the end, the proposed control scheme is demonstrated by a formation flying mission of four quadrotors with 2-DOF manipulators.

Keywords: Guidance navigation and control, Autonomous robotic systems, Robotics technology
Abstract: The structure of a space target and estimates of its relative pose (position and orientation) and motion are the primary first tasks of any formation flight, including missions to remove space debris. Acquiring these estimates for high-speed tumbling objects is very challenging, due to the lack of prior information about the target's structure and motion.

This paper proposes a method to estimate the relative position, linear and angular velocities, and attitude of space debris, based on vision measurements. The suggested approach employs a stereo camera to track a set of feature points on the target spacecraft, and an Unscented Kalman Filter (UKF) to perform the estimation procedure. The projection of tracked feature points on the two cameras creates an observation model of the filters and the structure of a non-cooperative spacecraft was determined by estimating the feature points' position. The relative attitude estimation is derived through the Modified Rodrigues Parameters (MRPs). A number of numerical simulations were conducted to validate the accuracy and stability of this solution, and the results indicated acceptable convergence of estimation errors for pose and motion estimation.

Keywords: Networked robotic system modeling and control, Mobile robots, Autonomous robotic systems
Abstract: This work is the first part of a project that is intended to develop a control strategy for multiple heterogeneous robots oriented to the assistance in situations of search and rescue. The project is presented from two perspectives that run simultaneously but in different time scales, the first is the real time heterogeneous robots control perspective in charge of the robots task execution studied mainly through the perspective of artificial potential functions and the second the task allocation problem in charge of the optimization of the number of people helped. This paper is intended to present the advance of the project in the area of real time control focused in the task of exploration considering the heterogeneity of the velocity of the robots, its limitations in communication range and the obstacles evasion. The algorithm presented allows the robots to explore a non-convex scene without losing the network connectivity, without presenting collisions between robots or between obstacles and introducing a simple network reconfiguration algorithm intended to make more flexible the network structure.

Keywords: Optimization and control of large-scale network systems, Efficient strategies for large scale complex systems, Complex logistic systems
Abstract: We present a graph theoretical approach for matching transports in a cooperative full-truckload network to prevent empty runs. In the simplest case of application so-called simple cycles are used to characterize matchings in directed and undirected graphs. These particular solutions allow estimates for the minimal and maximal solution of the whole optimization problem and can be used to calculate the optimal solution of the overall problem.

Keywords: Decentralized and distributed control, Modelling and decision making in complex systems, Complex logistic systems
Abstract: In this work, we propose a sequential distributed MPC algorithm for control of a linear supply chain. The algorithm is developed by closely taking into account supply chain specifics and requirements from practice, e.g., orders and leavings are both treated as decision variables at each stage and communication between stages is kept low. We present the rather surprising result that terminal equality constraints employed in the local MPC formulations are inherently satisfied for the overall system, despite the presence of bilateral dynamic couplings and solving the local MPC problems sequentially. This is due to the stock and flow nature of the problem. The proposed algorithm is shown to be recursively feasible, to asymptotically satisfy a constant customer demand and to achieve asymptotic convergence of the local stock and backlog to the desired levels. This is illustrated by numerical simulations.

Keywords: Production planning and control, Flexible and reconfigurable manufacturing systems, Job and activity scheduling
Abstract: Complex stochastic job-shop scheduling problems can be handled by simulation-based optimization (SBO), combining the optimization capabilities of meta-heuristics with the system representativeness of simulation models. In order to explore the potential of coupling optimization and simulation techniques in different job shop scheduling scenarios, this paper presents some of the ideas on an ongoing research project developing an SBO strategy coupling genetic algorithm and discrete-event simulation. Furthermore, this paper describes an approach to aid in the analysis of computed schedule feasibility subject to stochastic behavior, which is the case for most of the real world industries. One of the research goals is to provide an efficient and effective way to evaluate schedule robustness and to find robust schedules. The research may significantly contribute to businesses where scheduling changes are expensive, like in airline and train companies and automakers industries and suppliers.

Keywords: Complex logistic systems, Modelling and control of hybrid and discrete event systems, Modelling and decision making in complex systems
Abstract: This paper provides a mathematical model and a contribution to the discussion of the problem of queues and waiting times at loading/unloading ramps as a part of transportation networks. As a central point, the paper investigates how the waiting time can be reduced by adding additional empty trailers to the logistics system, and under the assumption that the trailers can be exchanged by the drivers. The proposed model can be used for further investigations and estimates in the cost benefit analysis, on the reduction of CO2 emission and other related issues.

Keywords: Life-cycle control, Flexible and reconfigurable manufacturing systems, Digital enterprise
Abstract: This paper is aimed at considering supply chain and related data management within an integrated vision of the product lifecycle management (PLM) implemented through the unified approach which is proper to the Industry 4.0 initiative. In particular, with the proposed manufacturing system architecture, decision support tools can use a unified repository fed by a factory replication application, powered by data from the field, even from remote production units. Such data allow to monitor the behaviour of the digital twin of the real machine and produces a digital twin of the real product, incorporating its actual characteristics measured by means of suitable acquiring systems (in the treated example: a 3D laser scanner). Moreover, it is provided a description of the plant technological subsystems that allow to share designing and manufacturing activities across multiple similar units located in remote areas. In this context of virtual enterprise, the supply chain management results as a key factor in enabling a cooperative approach.

Keywords: Production planning and control, Job and activity scheduling, Modeling of manufacturing operations
Abstract: In this paper, a long-term production planning problem is considered with the objective criteria Cmax and Tmax and under resource capacity and precedence constraints. The case study presented is characterized by four years planning horizon, 3552 operations, 51 workers and 57 units of equipment. The solution method elaborated in this study is a heuristic algorithm. Its performances are evaluated in numerical experiments. New procedures for makespan and resource load estimation are developed in order to identify bottleneck resources. The makespan estimation algorithm is tested on the well-known PSPLIB benchmark library where the best known lower bounds are improved for 5 instances. This procedure can also be used for the estimation of the gap from optimal value of the makespan time provided by the heuristic algorithm.

Keywords: Monitoring and performance assessment
Abstract: Non-linear time series analysis based methods are a popular choice for industrial control loop data analysis. In this paper a delay vector variance (DVV) based approach is presented to analyze the source of oscillations in an industrial control loop. The method is capable of differentiating between the linear and non-linear causes of oscillations and can also help in isolating the source of non-linearity. The automatic determination of embedding dimensions is augmented with the DVV analysis to make it more robust and reliable. The efficacy of the proposed method is established using simulation as well as industrial case studies.

Keywords: Monitoring and performance assessment, Signal and identification-based methods, Artificial intelligence
Abstract: Structural Health Monitoring (SHM) can be dened as the process of acquiring and analyzing data from on-board sensors to evaluate the health of a structure. Classically, an SHM process can be performed in four steps: detection, localization, classication and quantication. This paper addresses damage quantication issue as a classication problem whereby each class corresponds to a certain damage extent. Starting from the assumption that damage causes a structure to exhibit nonlinear response, we investigate whether the use of nonlinear model based features increases classication performance. A support Vector Machine (SVM) is used to perform multi-class classication task. Two types of features are used as inputs to the SVM algorithm: Signal Based Features (SBF) and Nonlinear Model Based Features (NMBF). SBF are rooted in a direct use of response signals and do not consider any underlying model of the test structure. NMBF are computed based on parallel Hammerstein models which are identied with an Exponential Sine Sweep (ESS) signal. A study of the sensitivity of classication performance to the noise contained in output signals is also conducted. Dimension reduction of features vector using Principal Component Analysis (PCA) is carried out in order to nd out if it allows robustifying the quantication process suggested in this work. Simulation results on a cantilever beam with a bilinear torsion spring stiness are considered for demonstration. Results show that by introducing NMBF, classication performance is improved. Furthermore, PCA allows for higher recognition rates while reducing features vector dimension. However, classiers trained on NMBF or on principal components appear to be more sensitive to output noise than those trained on SBF.

Keywords: Estimation and fault detection, Statistical methods/signal analysis for FDI, Industrial applications of process control
Abstract: Oscillations occurring in industrial process plants are often indicators of severe disturbances affecting the process operation. An accurate detection of oscillations is therefore of great interest for the economic viability of the process operation. The use of standard established oscillation detection methods requires however that the analysed signals fulfil conditions that are not always met in practice. A typical example is the presence of transient changes superposed to the oscillation pattern. This paper proposes simple heuristic methods to effectively detect and remove two types of commonly encountered transient changes (step changes and spike changes) from oscillatory signals. The effectiveness of the approach is analysed and the subsequent performance improvements of a standard oscillation detection method: the auto-correlation function method (Thornhill et al., 2003) is demonstrated. The approach is carried out on a 1,3-Butadiene production process where several measurements showed an established oscillation occurring after a production level change.

Keywords: Monitoring and performance assessment, Process control applications, Process performance monitoring/statistical process control
Abstract: We propose a model-plant mismatch (MPM) detection strategy based on a novel closed-loop identification approach and one-class support vector machine (SVM) learning technique. With this scheme we can monitor MPM and noise model change separately, thus discriminating the MPM from noise model change. Another advantage of this approach is that it is applicable to routine operating data that may lack any external excitations. Theoretical derivations on the closed-loop identification method are provided in this paper, showing that it can furnish a consistent parameter estimate for the process model even in the case where a priori knowledge about the true noise model structure is not available. We build an SVM model based on process and noise model estimates from training data to predict the occurrence of MPM in the testing data. An example on paper machine control is provided to verify the proposed MPM detection framework.

Keywords: Monitoring and performance assessment, Process modeling and identification, Process control applications
Abstract: Partial least squares and canonical correlation analysis are latent variable models suitable for quality-relevant monitoring based on process and quality data. Recently, concurrent monitoring schemes are also proposed to achieve comprehensive quality-relevant monitoring. This paper defines and analyzes quality-relevant monitoring based on these popular latent structure modeling methods, and the associated quality-relevant detection statistics are defined. Additionally, contribution plots and reconstruction-based contribution diagnosis methods are developed for concurrent CCA based fault diagnosis. Multi-dimensional quality-relevant faults can be diagnosed in the same reconstruction framework. Finally, a detailed case study on Tennessee Eastman process is shown to illustrate the diagnosis of process and quality faults and the prognosis of quality-relevant faults.

Keywords: Estimation and fault detection, Monitoring and performance assessment
Abstract: Multivariate statistical process monitoring methods aim at detecting and identifying faults in the performance of processes over time in order to keep the process under control. Singular spectrum analysis (SSA) is a promising tool for multivariate process monitoring. It allows the decomposition of dynamic process variables or time series into additive components that can be monitored separately to identify hidden faults that may otherwise not be detectable. However, SSA is a linear method and can give misleading information when it is applied to dynamic processes with strong nonlinearity. Therefore, in this paper, nonlinear versions of SSA based on the use of autoassociative neural networks or autoencoders and dissimilarity matrices are considered. This is done based on the benchmark Tennessee Eastman process that is widely used in the evaluation of statistical process monitoring methods

Keywords: Control of systems in vehicles, Decentralized Control and Systems, Decision making and autonomy, sensor data fusion
Abstract: This paper proposes a flight array system and an integrated approach to cope with its operational issues raised in mission-planning level (i.e., task allocation) and control level (i.e., control allocation). The proposed flight array system consists of multiple ducted-fan UAVs that can assemble with each other to fly together, as well as dissemble themselves to fly individually for accomplishing a given mission. To address the task allocation problem, a game-theoretical framework is developed. This framework enables agents to converge into an agreed task allocation in a decentralised and scalable manner, while guaranteeing a certain level of global optimality. In addition, this paper suggests a cooperative control scheme based on sliding mode control and weighted pseudo-inverse techniques so that the system's non-linearity and control allocation issue are effectively handled. As a proof-of-concept, a prototype simulation program is developed and validated in a cooperative jamming mission. The numerical simulations manifest the feasibility of effectiveness of the proposed approach.

Keywords: Localization, Multi-vehicle systems, Cooperative navigation
Abstract: This paper presents a novel approach for localising a GPS (Global Positioning System)-denied Unmanned Aerial Vehicle (UAV) with the aid of a GPS-equipped UAV in three-dimensional space. The GPS-equipped UAV makes discrete-time broadcasts of its global coordinates. The GPS-denied UAV receives the broadcast and in doing so takes a direction of arrival (DOA) measurement towards the origin of the broadcast in its local coordinate frame (obtained via an inertial navigation system (INS)). The aim is to determine the difference between the local and global frames, described by a rotation and a translation. In the noiseless case, global coordinates are recovered exactly by solving a system of linear equations. When DOA measurements are contaminated with noise, rank relaxed semidefinite programming (SDP) and the Orthogonal Procrustes algorithm are employed. Simulations are provided and factors affecting accuracy, such as noise levels and number of measurements, are explored.

Keywords: Multi-vehicle systems, Cooperative control, Cooperative navigation
Abstract: This paper addesses the problem of formation control in multi-agent systems. It is inspired by recent results by Qingkai et al. and adopts an event-triggered control strategy to reduce the number of communications between agents. For that purpose, to evaluate its control input, each agent maintains estimators of the states of the other agents. Communication is triggered when the discrepancy between the actual state of an agent and the corresponding estimate reaches some threshold. The impact of additive state perturbations on the formation control is studied. A condition for the convergence of the multi-agent system to a stable formation is studied. Simulations show the effectiveness of the proposed approach.

Keywords: Flight dynamics identification, formation flying, Autonomous systems, Guidance, navigation and control of vehicles
Abstract: As Unmanned Aerial Vehicles (UAVs) become more readily available and reduce in cost, using multiple UAVs simultaneously to accomplish a task becomes increasingly attractive. Once swarms of UAVs share the same workspace (operational environment) it is necessary to have a means to rapidly adopt an optimal collision-free formation in the workspace. A popular approach for formation of an optimal swarm is to use Particle Swarm Optimization (PSO) techniques. A variant of PSO was recently introduced called nPSO which claims to exhibit more rapid convergence than other variants. In this paper nPSO is applied to the problem of finding optimal positions of UAVs forming a swarm in presence of large obstacles such as buildings in an urban environment. The experiments show that no more than 1000 iterations are required to obtain near optimal formation of swarm of UAVs for different maps, including maps relating to congested environments.

Keywords: Trajectory and Path Planning, Multi-vehicle systems, Cooperative navigation
Abstract: This paper presents the development of a path-planning algorithm for Unmanned Aerial Vehicles (UAVs) in order to increase the situational awareness for platooning vehicles. The scenario considers a team of cooperative UAVs, initially docked on moving Unmanned Ground Vehicles (UGVs). In particular, the goal consists in finding the best routing plan for the UAVs in order to visit some designated targets in a wide search area to augment the UGVs’ situational awareness. Taking into account the maximal endurance constraint of the UAVs, this problem becomes equivalent to a time-constrained multiple depot vehicle routing problem with moving depots. To tackle this variant of the well-known vehicle routing problem, a methodology based on a TABU search meta-heuristic is implemented. While respecting the endurance constraint, this methodology tempts to optimize multiple objectives: the number of UAVs required, the total length of the routing and the balance of the lengths of the different routes within the routing plan. The proposed approach based on a meta-heuristic gives relevant results in a relatively short period of time.

Keywords: Trajectory and Path Planning, Multi-vehicle systems, Autonomous Mobile Robots
Abstract: This paper addresses a UAV path planning problem for a team of cooperating heterogeneous vehicles composed of one unmanned aerial vehicle (UAV) and multiple unmanned ground vehicles (UGVs). The UGVs are used as mobile actuators while the UAV serves as a messenger to achieve information sharing among the UGVs. The UAV needs to fly over each UGV periodically to collect the information and then transmit the information to the other UGVs. The UAV path planning problem with messenger mechanism is formulated as a Dynamic Dubins Traveling Salesman Problem with Neighborhood (DDTSPN). The goal of this problem is to find the shortest route enabling the UAV to deliver information to all requested UGVs. When solving this path planning problem, a decoupling strategy is introduced to sequentially determine the access sequence of UGVs for UAV and the access location of UAV in the communication neighborhood of each UGV. The effectiveness of the proposed approach is corroborated through computational experiments on several randomly generated instances.

Keywords: Innovation (in development contexts), Service Engineering Applications
Abstract: This paper deals with fleet management and maintenance planning concepts for industrial vehicles by taking into account the operational constraints, the missions planning and the health state of each vehicle of the fleet. The objective is to schedule the different maintenance operations according to the vehicle availability to prevent them for failing during a mission. The joint planning between maintenance and missions has to optimize the profit of the hauler and reduce the maintenance costs. At the end, by knowing the vehicles health state, the missions’ characteristics and the conditions of use, each vehicle is allocated to a schedule to reach the objectives defined by the hauler. Each schedule corresponds to missions interspersed by maintenance operations. The industrial objectives and challenges regarding maintenance and fleet management are first detailed and actual present maintenance practice is assessed. Then, the latest developments on these two topics are presented, which allows the definition of our research perspectives.

Keywords: Control and Automation Systems failure
Abstract: Fault detection and isolation based on hybrid approaches have been an active field of research over the last few years. From a practical point of view, the development of generic and unified approaches for industrial supervision systems design is a key challenge. The main methodological contribution of the present work is to develop a hybrid approach properly tailored for such challenge. The proposed approach uses the Bond Graph formalism to systematically develop computational models and algorithms for robust fault detection and isolation. The resulting outcomes are extended to a proposed data-driven approach which consists of transforming historical process data into a meaningful alphabetical model incorporated within a Bayesian network. This new hybrid methodology benefits from all the knowledge available on the system and provides a more comprehensive solution in order to increase the overall confidence in the diagnosis and the performances. The effectiveness of the developed hybrid approach is validated by the well-known Tennessee Eastman Benchmark process.

Keywords: Renewable Energy System Modeling and Integration
Abstract: All technical processes are subject to dysfunctions during their lifespan, and large solar thermal systems (LSTS) are no exception to this rule. The development of robust fault detection and isolation (FDI) methods is therefore a key issue. This paper presents a comparison between what can be used and what is currently used for FDI in LSTS. We show that there is a way for new developments and improvements of the detection and identication of faults in LSTS. Based on this observation, a scheme which combines several methods for feature generation and fault diagnosis is proposed. Future developments for each part of this scheme are presented regarding their utility.

Keywords: Systems Theory
Abstract: In this extended abstract, a bibliography review about the identification of timed discrete-event systems (DES) is presented as part of the beginning of a PhD thesis. Some existing approaches for untimed DES, modeled by Petri nets (PNs) or automata, are first reviewed. Next, recent proposals are introduced for the identification of timed DES. This review leads us to formulate directions for our future work.

Keywords: Complexity modelling
Abstract: The objective of the PhD thesis is to adapt different human diseases propagation models (like Human HIV or Malaria, heart failure, kidney stones to give some examples) to production systems by: i) firstly, realize an analogy between biological and industrial systems; ii) secondly extend chosen research works in bio-mathematics models of diseases propagation phenomena to production systems; iii) based on the proposed model, analyse the production system dynamics and performances under disruptions events (like failures, pollutions, non- continuous electricity supply, etc.) and iv) propose optimal policies to improve the overall system in case of troublesome events. In a first step, described in this paper, we will consider a production resource. Then, we will generalize our results to more complex production systems (like transfer lines, assembling / disassembling lines, etc.). So, the main objective of this paper is to propose a disruptive phenomenon propagation model for a simple production resource which could be a special machining or device. For this, we define three kinds of components for the production machine: “susceptible”components which could fail easily if a disruptive phenomenon occurs (as a significant increase in temperature, an electrical overload, a failure of a crucial component of the production resource, etc.), “non- susceptible”components which are protected against the phenomenon and faulty components which are already affected by the phenomenon. Then, based on a SIR bio-mathematical model of HIV propagation, we propose a corresponding model for the considered production resource. Then, we observe the impact of this propagation model on the overall production system.

Keywords: Renewable Energy System Modeling and Integration
Abstract: Abstract: The extended abstract seeks to contribute towards the scientific arena of conditional and predictive wind turbine maintenance, in particular reference to the industrial context where the goal is to detect failures in advance in order to reduce maintenance costs. Modern industrial problems and challenges include huge maintenance costs and need for a better maintenance approach. Comparison of major monitoring and fault diagnosis approaches explain the problem statement while the state of the art, along with some implementation results give further insight to the limitations and research challenges. The industrial and scientific objectives of the proposed research work include diagnosis of the nature of the fault to adapt the maintenance strategy, generalization to other operating and environmental conditions (site / turbine), use of external data and merging of indicators created using developed algorithm.

Keywords: Urban Mobility
Abstract: This paper presents the development stages of a method to detect the faults occurring in a proton exchange membrane fuel cell (PEMFC) using a model based approach. After fitting the model, the generation and evaluation of a residual allows the detection of some faulty conditions of the fuel cell. The increase of the number of residuals using electrochemical spectroscopy will enable a better detection and identification of faults. The further steps of the methodology are the integration of the dynamic operating conditions of the fuel cell, moreover, the ageing of the fuel cell must be assessed to provide a diagnosis that takes into account the fuel cell degradations. Finally, the algorithm must work in real time for an instantaneous response of the control system, thus a fast-computing algorithm is needed.

Keywords: Intelligent Transportation
Abstract: We propose in this paper a methodological synthesis of discrete controllers needed for railway automation, especially to avoid collisions in railway nodes. The automation and the adoption of ERTMS (European Rail Traffic Management System) are two solutions for railway systems to increase the capacity of railway lines and to enhance their safety. In this study we use finite state machines for modeling and Supremica tool for the synthesis of controllers.

Keywords: Control and Automation Systems failure
Abstract: Industrial Control Systems (ICS) have become a new target of attackers since the beginning of the century. Computer worm Stuxnet proved the vulnerability of these systems to cyber-attacks. Control-command architecture is built to ensure the safety and the reliability of the system and the environment, however, several attacks or studies have underlined the lack of protection of components in an ICS. They equally proved the incomplete solutions proposed by the Information technology (IT). This paper presents an innovative approach for intrusion detection system in ICS based on the notions of states and distance between sets of states. Distance assessment over time between common and forbidden states of the system provides the prediction and discrimination of deviations. A proposed algorithm analyses orders sent to actuators continuously and enables to stop dangerous orders for the system. This study is supported by simulations inspired by classical ICS.

Keywords: Systems Theory
Abstract: Testing is a fundamental technique for system design and verification, however its application to discrete event systems modeled by unbounded synchronized Petri nets challenges that there exists no finite faithful representation for the infinite state space of these models. In this paper, we consider a special class of 1-place-unbounded synchronized Petri nets, that contain a single unbounded place. We first develop an improved modified coverability graph that precisely represents the state space of such a model, then unfold the computation work of synchronizing sequences and homing sequences based on this new graph.

Keywords: Intelligent Transportation
Abstract: The real-time Ethernet in deterministic networks is far from being safe, it guarantees perfect synchronization among devices, and meets the real-time requirements but not the safety ones. To ensure these requirements, we need to identify the errors in the digital communication. In order to add safety measures in the communication system, this paper describes an analysis of IEC 61508 and IEC 61784. Furthermore, we propose to implement a safety layer over Real-Time Ethernet (at the top of the application layer) in the embedded real-time systems.

Keywords: Evoluationary computing in business and social systems, Descriptive Analytics
Abstract: This paper is dedicated to the study of the performance of the Bayesian based Evolutionary Algorithm (BEA) regarding the quantity of the archive needed to have an efficient selection strategy process. Indeed, BEA is based on the use of a dynamic mechanism to change the search strategy (crossover and mutation) during its evolution. To do so, it selects the most probable strategy from those possible ones based on the Bayes rule periodically. Experiments were performed on classical continuous optimization problems and benchmarks. Obtained results showed that for a given class of problems a fixed archive size is suited to do Bayes based selection strategy.

Keywords: Fractional systems
Abstract: Controlling of the temperature of a thermal medium remains of a great importance because of the economic cost that it may engender. Thus, one effective way to reduce heating/cooling cost is by providing a good control system that limits power needed to run these tasks. For this purpose, we will present in this paper the control of a finite homogeneous diffusive interface using the third generation CRONE controller and control its behavior to the PID controller. The novelty of this work exists in the use of a fractional order controller (the CRONE controller) applied to a fractional order plant and the use of a complex controller (the third generation) which is not so familiar in the controllers domain. The results show that the behavior and the robustness of the CRONE controller are better than the PID controller.

Keywords: Fractional systems, Delay systems, Adaptive control
Abstract: In this paper, pinning synchronization of fractional general complex dynamical networks with time delay is investigated. Based on the stability theory of fractional systems and the inequality of the fractional derivative, some pinning synchronization criteria are abtained for both directed and undirected complex networks. Moreover, an adaptive pinning controller is designed to achieve synchronization of fractional general complex networks with time delay. Finally, some numerical examples are given to verify the proposed theoretical analysis.

Keywords: Fractional systems, Control in system biology, Systems biology
Abstract: Bone is a living tissue undergoing a constant remodeling process that involves different cell types, in particular osteoclasts and osteoblasts. This process can be modeled using differential equations, accounting for the biochemical coupling between the referred bone cells. These models have also been extended to include the effects of bone diseases in its dynamics, such as tumor metastizations.

Due to the high number of parameters involved in the existing physiological models for bone remodeling, a new approach to this system is here presented. Variable order derivatives are introduced as a method to simplify its structure, providing more compact models that lead to similar results to those of the original formulations. These new models also allow for anomalous diffusion to be accounted for.

These models are expected to serve in clinical decision systems such as personalized therapy schemes.

Keywords: Fractional systems, Positive systems, Linear systems
Abstract: This paper introduces and characterizes linear positive fractional variable order discrete-time systems described in pseudo state-space form for different types of fractional variable order differences. The verifiable necessary and sufficient conditions of positivity are also given.

Keywords: Fractional systems, Linear systems, Time-varying systems
Abstract: This paper is concerned with fractional-order iterative learning control (ILC) for the tracking problems of a class of linear time-varying systems. Both open-loop and closed-loop PD-type iterative learning updating laws are considered. Sufficient conditions for the convergence of the tracking errors are obtained. Finally, the efficiency of the methods are verified by numerical simulations.

Keywords: Fractional systems, Optimal control theory, Output regulation
Abstract: In this paper an optimal design method for the tuning of the fractional order proportional-integral-derivative-acceleration (PIλDµA) controller parameters is presented. The fractional order PIλDµA controller is a conventional proportional-integral-derivative-acceleration (PIDA) controller whose integration action order λ and differentiation action order μ are real rather than integer. The two more parameters λ and μ will provide a better flexibility in controller design for a wide range of dynamical systems. The six parameters of the fractional order PIλDµA controller are tuned through the optimization of the Integral Time Absolute Error (ITAE) performance criteria using the Particle Swarm Optimization (PSO) algorithm. The fractional order PIλDµA controller design for two real world system models of a feedback control system have been proposed to illustrate its benefits and effectiveness. The simulation results show that the proposed fractional PIλDµA controller exhibits dynamical performances improvements compared to the conventional PIDA controller of the feedback control system.

Keywords: Fractional systems, Large scale optimization problems, Differential or dynamic games
Abstract:

Reverse Ishikawa-Nesterov's algorithm is one of the speedup techniques for finding best response set in mean-field games. However, the convergence rate was not examined so far. In this work, we evaluate the convergence rate and convergence time of reverse Ishikawa-Nesterov learning scheme for a deterministic fractional mean-field games. The fractional mean-field game problem given by a fractional controlled state dynamics and payoff that measures the gap between a mean-field term and the fractional integral of the state. First, we prove that the problem is well-posed and has a unique best response to mean-field. Second, we derive conditions for convergence of the reverse Ishikawa-based learning scheme and provide the error gap. Finally, we show that the reverse Ishikawa-Nesterov's technique outperforms the standard descent methods.