Stabilization of Aperiodic Sampled-data Linear Systems with Input Constraints: a Low Complexity Polyhedral Approach - Université Grenoble Alpes
Communication Dans Un Congrès Année : 2021

Stabilization of Aperiodic Sampled-data Linear Systems with Input Constraints: a Low Complexity Polyhedral Approach

Résumé

The stabilization problem of aperiodic sampleddata linear systems subject to input constraints is dealt with. A state feedback control law is designed to optimize the size of a polyhedral estimate of the region of attraction of the origin (RAO) of the closed-loop system. The control law is derived from the computation of a controlled contractive polytope for the dynamics between two successive sampling instants. The polytope is of low complexity as its number of vertices is fixed a priori. As shown in the numerical example, the polyhedral estimate of the RAO associated with the proposed feedback control is larger than the ones obtained with other approaches in the literature.
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Dates et versions

hal-03361476 , version 1 (01-10-2021)

Identifiants

Citer

Daniel Denardi Huff, Mirko Fiacchini, João Manoel Gomes da Silva. Stabilization of Aperiodic Sampled-data Linear Systems with Input Constraints: a Low Complexity Polyhedral Approach. CDC 2021 - 60th IEEE Conference on Decision and Control, Dec 2021, Austin, Texas, United States. ⟨10.1109/CDC45484.2021.9683136⟩. ⟨hal-03361476⟩
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