Derivative-Based Sampled Data Control for Continuous Linear Parameter Varying System With Unknown Parameters

Sonia Maalej (1) , Alexandre Kruszewski (2, 3) , Lotfi Belkoura (4)

1 CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189
2 Centrale Lille
3 DEFROST - Deformable Robots Simulation Team
4 SyNeR - Systèmes Non Linéaires et à Retards

This paper deals with the robust stabilization of a class of linear parameter varying (LPV) systems in the sampled data control case. Instead of using a state observer or searching for a dynamic output feedback, the considered controller is based on output derivatives estimation. This allows the stabilization of the plant with very large parameter variations or uncertainties. The proof of stability is based on the polytopic representation of the closed-loop under Lyapunov conditions and system transformations. The result is a control structure with only one parameter tuned via very simple conditions. Finally, the effectiveness of the proposed method is verified via a numerical example of a second-order LPV system.

Domaines: Automatique / Robotique; Automatique

Sonia Maalej, Alexandre Kruszewski, Lotfi Belkoura. Derivative-Based Sampled Data Control for Continuous Linear Parameter Varying System With Unknown Parameters. Journal of Dynamic Systems, Measurement, and Control, 2019, 141 (8), pp.081013. ⟨10.1115/1.4042947⟩. ⟨hal-02403902⟩