State and Unknown Inputs Estimations for Multi-Model descriptor Systems

Hamdi Habib (1) , Chokri Mechmeche (1) , Mickael Rodrigues (2) , Naceur Benhadj Braiek (1)

1 INSAT - Institut National des Sciences Appliquées et de Technologie [Tunis]
2 LAGEP - Laboratoire d'automatique et de génie des procédés

This paper examines the problem of the state and the unknown inputs estimation for nonlinear descriptor system via Unknown Input and Proportional Integral Observer (PIO). The used approach is based on the multi-model representation of the nonlinear descriptor process. The design methods of both proportional integral observers and unknown inputs observers for multi-model descriptor systems are described in detail. Sufficient existence conditions of both unknown input and PI observers are given and linear matrix inequalities (LMIs) are solved to design the gains of these observers. A numerical example is provided to illustrate and to compare the design developed in this paper.

Mots clés: LMIs; Nonlinear descriptor system; multimodel descriptor system; proportional integral and unknown input observer; LMIs.

Domaines: Automatique / Robotique

Hamdi Habib, Chokri Mechmeche, Mickael Rodrigues, Naceur Benhadj Braiek. State and Unknown Inputs Estimations for Multi-Model descriptor Systems. International Multi-Conference on Systems, Signals & Devices SSD11, Apr 2011, Sousse, Tunisia. pp.Proceedings. ⟨hal-00560111⟩