Predictor-based sampled-data exponential stabilization through continuous–discrete observers

Frédéric Mazenc 1, 2 Emilia Fridman 3
2 DISCO - Dynamical Interconnected Systems in COmplex Environments
L2S - Laboratoire des signaux et systèmes, Inria Saclay - Ile de France, SUPELEC, CNRS - Centre National de la Recherche Scientifique : UMR8506
Abstract : The problem of stabilizing a linear continuous-time system with discrete-time measurements and a sampled input with a pointwise constant delay is considered. In a first part, we design a continuous-discrete observer which converges when the maximum time interval between two consecutive measurements is sufficiently small. In a second part, we construct a dynamic output feedback by using a technique which is strongly reminiscent of the reduction model approach. It stabilizes the system when the maximal time between two consecutive sampling instants is sufficiently small. No limitation on the size of the delay is imposed and an ISS property with respect to additive disturbances is established.
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Frédéric Mazenc, Emilia Fridman. Predictor-based sampled-data exponential stabilization through continuous–discrete observers. Automatica, Elsevier, 2016, 63, pp.7. ⟨10.1016/j.automatica.2015.10.016⟩. ⟨hal-01248072⟩

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