Necessary and Sufficient Convex Condition for the Stabilization of Linear Sampled-data Systems under Poisson Sampling Process - Université Grenoble Alpes
Article Dans Une Revue IEEE Control Systems Letters Année : 2022

Necessary and Sufficient Convex Condition for the Stabilization of Linear Sampled-data Systems under Poisson Sampling Process

Résumé

This work presents a control design method for linear sampled-data systems whose random sampling intervals form a Poisson process. Unlike a previous result in the literature, the proposed stabilization conditions, based on linear feedbacks of both the state and the past input values, are necessary and sufficient for the mean exponential stability of the system. Moreover, such non-conservative conditions correspond to linear matrix inequalities, implying then that the stabilization problem can be efficiently addressed through semidefinite programming. As a second contribution, the characterization and optimization of the mean exponential convergence rate of the closed-loop system is given in form of a generalized eigenvalue problem. A numerical example illustrates the theoretical results.
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Dates et versions

hal-03706820 , version 1 (28-06-2022)

Identifiants

Citer

Daniel Denardi Huff, Mirko Fiacchini, Joao Manoel Gomes da Silva Jr.. Necessary and Sufficient Convex Condition for the Stabilization of Linear Sampled-data Systems under Poisson Sampling Process. IEEE Control Systems Letters, 2022, 6, pp.3403-3408. ⟨10.1109/LCSYS.2022.3184902⟩. ⟨hal-03706820⟩
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