116 research outputs found

    Set theory conditions for stability of linear impulsive systems

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    International audience— In this paper we give tractable necessary and sufficient condition for the global exponential stability of a linear impulsive system. The reset rule considered in the paper is quasi-periodic and the stability analysis is based on a standard tool in set theory that is Minkowski functional. Firstly, we reformulate the problem in term of discrete-time parametric uncertain system with the state matrix belonging to a compact but non-convex set. Secondly, we provide a tractable algorithm for testing the stability and computing the associated polyhedral Lyapunov function when the system is stable. The main result is an algorithm whose computational effort is analogous to that of classical algorithms for contractive polytopes computation for discrete-time parametric uncertain systems with the state matrix belonging to a polytopic set

    Computing control invariant sets is easy

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    In this paper we consider the problem of computing control invariant sets for linear controlled systems with constraints on the input and on the states. We focus in particular on the complexity of the computation of the N-step operator, given by the Minkowski addition of sets, that is the basis of many of the iterative procedures for obtaining control invariant sets. Set inclusions conditions for control invariance are presented that involve the N-step sets and are posed in form of linear programming problems. Such conditions are employed in algorithms based on LP problems that allow to overcome the complexity limitation inherent to the set addition and can be applied also to high dimensional systems. The efficiency and scalability of the method are illustrated by computing in less than two seconds an approximation of the maximal control invariant set, based on the 15-step operator, for a system whose state and input dimensions are 20 and 10 respectively

    Computation of Robust Control Invariant Sets with Predefined Complexity for Uncertain Systems

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    This paper presents an algorithm that computes polytopic robust control-invariant (RCI) sets for rationally parameter-dependent systems with additive disturbances. By means of novel LMI feasibility conditions for invariance along with a newly developed method for volume maximization, an iterative algorithm is proposed for the computation of RCI sets with maximized volumes. The obtained RCI sets are symmetric around the origin by construction and have a user-defined level of complexity. Unlike many similar approaches, fixed state feedback structure is not imposed. In fact, a specific control input is obtained from the LMI problem for each extreme point of the RCI set. The outcomes of the proposed algorithm can be used to construct a piecewise-affine controller based on offline computations

    Nonlinear Set Membership Filter with State Estimation Constraints via Consensus-ADMM

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    This paper considers the state estimation problem for nonlinear dynamic systems with unknown but bounded noises. Set membership filter (SMF) is a popular algorithm to solve this problem. In the set membership setting, we investigate the filter problem where the state estimation requires to be constrained by a linear or nonlinear equality. We propose a consensus alternating direction method of multipliers (ADMM) based SMF algorithm for nonlinear dynamic systems. To deal with the difficulty of nonlinearity, instead of linearizing the nonlinear system, a semi-infinite programming (SIP) approach is used to transform the nonlinear system into a linear one, which allows us to obtain a more accurate estimation ellipsoid. For the solution of the SIP, an ADMM algorithm is proposed to handle the state estimation constraints, and each iteration of the algorithm can be solved efficiently. Finally, the proposed filter is applied to typical numerical examples to demonstrate its effectiveness

    Techniques de détection de défauts à base d’estimation d’état ensembliste pour systèmes incertains

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    This thesis proposes a new Fault Detection approach for linear systems with interval uncertainties, bounded perturbations and bounded measurement noises. In this context, the Fault Detection is based on a set-membership state estimation of the system. The main contributions of this thesis are divided into three parts:- The first part proposes an improved method which combines the good accuracy of the zonotopic set-membership state estimation and the reduced complexity of the ellipsoidal set-membership estimation.- In the second part, a new ellipsoidal state estimation approach based on the minimization of the ellipsoidal radius is developed, leading to Linear Matrix Inequality optimization problems. In this context, both multivariable linear time-invariant systems and linear time-variant systems are considered. An extension of these approaches to systems with interval uncertainties is also proposed. - In the continuity of the previous approaches, two Fault Detection techniques have been proposed in the third part based on these set-membership estimation techniques. The first technique allows to detect sensor faults by checking the consistency between the model and the measurements. The second technique is based on Multiple Models. It deals with actuator/component/sensor faults in the same time. A Min-Max Model Predictive Control is developed in order to find the optimal control and the best model to use for the system in spite of the presence of these faults.Cette thèse propose une nouvelle approche de détection de défauts pour des systèmes linéaires soumis à des incertitudes par intervalles, des perturbations et des bruits de mesures bornés. Dans ce contexte, la détection de défauts est fondée sur une estimation ensembliste de l'état du système. Les contributions de cette thèse concernent trois directions principales :- La première partie propose une méthode d'estimation d'état ensembliste améliorée combinant l'estimation à base des zonotopes (qui offre une bonne précision) et l'estimation à base d'ellipsoïdes (qui offre une complexité réduite).- Dans la deuxième partie, une nouvelle approche d'estimation d'état ellipsoïdale fondée sur la minimisation du rayon de l'ellipsoïde est développée. Dans ce cadre, des systèmes multivariables linéaires invariants dans le temps, ainsi que des systèmes linéaires variants dans le temps ont été considérés. Ces approches, résolues à l'aide de problèmes d'optimisation sous la forme d'Inégalités Matricielles Linéaires, ont été étendues au cas des systèmes soumis à des incertitudes par intervalles.- Dans la continuité des approches précédentes, deux techniques de détection de défauts ont été proposées dans la troisième partie utilisant les méthodes d'estimation ensemblistes. La première technique permet de détecter des défauts capteur en testant la cohérence entre le modèle et les mesures. La deuxième technique fondée sur les modèles multiples permet de traiter simultanément les défauts actionneur/composant/capteur. Une commande prédictive Min-Max a été développée afin de déterminer la commande optimale et le meilleur modèle à utiliser pour le système, malgré la présence des différents défauts

    Efficient reachability analysis of parametric linear hybrid systems with time-triggered transitions

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    Efficiently handling time-triggered and possibly nondeterministic switches for hybrid systems reachability is a challenging task. In this paper we present an approach based on conservative set-based enclosure of the dynamics that can handle systems with uncertain parameters and inputs, where the uncertainties are bound to given intervals. The method is evaluated on the plant model of an experimental electro-mechanical braking system with periodic controller. In this model, the fast-switching controller dynamics requires simulation time scales of the order of nanoseconds. Accurate set-based computations for relatively large time horizons are known to be expensive. However, by appropriately decoupling the time variable with respect to the spatial variables, and enclosing the uncertain parameters using interval matrix maps acting on zonotopes, we show that the computation time can be lowered to 5000 times faster with respect to previous works. This is a step forward in formal verification of hybrid systems because reduced run-times allow engineers to introduce more expressiveness in their models with a relatively inexpensive computational cost.Comment: Submitte
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