A state dependent sampling for linear state feedback |
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Authors: | Christophe Fiter Laurentiu Hetel Wilfrid Perruquetti Jean-Pierre Richard |
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Affiliation: | 1. Laboratoire d’Automatique, Génie Informatique et Signal (CNRS UMR 8219), École Centrale de Lille, 59651 Villeneuve d’Ascq, France;2. Non-A, INRIA Lille-Nord Europe, France;1. Laboratoire des Signaux et Systèmes (L2S), CNRS, CentraleSupélec, Univ Paris-Sud, Université Paris-Saclay, 91192, Gif-sur-Yvette, France;2. Inria Saclay, team GECO & CMAP, École Polytechnique, CNRS, Université Paris-Saclay, Palaiseau, 91128, France;1. School of Electrical and Control Engineering, Henan University of Urban Construction, Pingdingshan, 467036, China;2. School of Electrical Engineering, Zhengzhou University, Zhengzhou, 45001, China;1. CRIStAL CNRS UMR 9189, Université Lille 1, 59650, Villeneuve d’Ascq, France;2. Defrost, INRIA - Lille Nord Europe, 40 avenue Halley, 59650, Villeneuve d’Ascq, France;3. QUARTZ EA 7393, ENSEA, 6 Avenue du Ponceau, 95014, Cergy Pontoise Cedex, France |
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Abstract: | In this work, a new state-dependent sampling control enlarges the sampling intervals of state feedback control. We consider the case of linear time invariant systems and guarantee the exponential stability of the system origin for a chosen decay rate. The approach is based on LMIs obtained thanks to sufficient Lyapunov–Razumikhin stability conditions and follows two steps. In the first step, we compute a Lyapunov–Razumikhin function that guarantees exponential stability for all time-varying sampling intervals up to some given bound. This value can be used as a lower-bound of the state-dependent sampling function. In a second step, an off-line computation provides a mapping from the state-space into the set of sampling intervals: the state is divided into a finite number of regions, and to each of these regions is associated an allowable upper-bound of the sampling intervals that will guarantee the global (exponential or asymptotic) stability of the system. The results are based on sufficient conditions obtained using convex polytopes. Therefore, they involve some conservatism with respect to necessary and sufficient conditions. However, at each of the two steps, an optimization on the sampling upper-bounds is proposed. The approach is illustrated with numerical examples from the literature for which the number of actuations is shown to be reduced with respect to the periodic sampling case. |
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