Fault detection, isolation and estimation for Takagi-Sugeno nonlinear systems - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Journal of The Franklin Institute Année : 2014

Fault detection, isolation and estimation for Takagi-Sugeno nonlinear systems

Résumé

This article is dedicated to the problem of fault detection, isolation and estimation for nonlinear systems described by a Takagi-Sugeno (T-S) model. One of the interests of this type of models is the possibility to extend some tools and methods from the linear system case to the nonlinear one. The principle of the proposed strategy is to transform the problem of simultaneously minimizing the perturbation effect and maximizing the fault effect, on the residual vector, in a simple problem of L2-norm minimization. A linear system is used to define the ideal response of the residual signal to the fault. Then the aim is to synthesize a residual generator that both minimizes the difference between real and ideal responses and the influence of the disturbance. The minimization problem is formulated by using the bounded real lemma (BRL) and linear matrix inequality (LMI) formalism. After studying the general framework, a special case of systems with actuator and sensor faults is considered where the fault incidence matrix is not full column rank. Simulation examples are given to illustrate the proposed method. Finally, Polya's theorem is used to reduce the conservatism of the proposed result. The obtained relaxation is also illustrated by a numerical example.
Fichier principal
Vignette du fichier
2014_JFI_ICHALAL_hal.pdf (843.74 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-00809844 , version 1 (27-02-2023)

Licence

Paternité - Pas d'utilisation commerciale - Pas de modification

Identifiants

Citer

Dalil Ichalal, Benoît Marx, José Ragot, Didier Maquin. Fault detection, isolation and estimation for Takagi-Sugeno nonlinear systems. Journal of The Franklin Institute, 2014, 351 (7), pp.3651-3676. ⟨10.1016/j.jfranklin.2013.04.012⟩. ⟨hal-00809844⟩
179 Consultations
28 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More