Title: Fuzzy observer for fault detection and reconstruction of unknown input fuzzy models

Authors: Mohammed Chadli, Abdelkader Akhenak, Didier Maquin, Jose Ragot

Addresses: Laboratoire de Modelisation, Information et systemes, Universite de Picardie – Jules Verne, 7, Rue du Moulin Neuf, Amiens 80000, France. ' Institut de Recherche en systemes electroniques embarques, Technopole du Madrillet, Avenue Gallilet, BP 10024, Saint Etienne du Rouvray Cedex 76801, France. ' CRAN, UMR 7039 CNRS-UHP-INPL, 2, Avenue de la foret de Haye, Vandoeuvre-les-Nancy Cedex 54516, France. ' CRAN, UMR 7039 CNRS-UHP-INPL, 2, Avenue de la foret de Haye, Vandoeuvre-les-Nancy Cedex 54516, France

Abstract: This paper addresses the design of a fuzzy observer for unknown input Takagi-Sugeno (T–S) fuzzy model. The main contribution of this paper is the development of a robust fuzzy observer in the presence of disturbances. Based on Lyapunov function, it is shown how to determine the observers gains in Linear Matrix Inequalities (LMI) terms. The proposed observer structure allows to estimate simultaneously and systematically the unknown inputs and state variables. The designed T–S observer is used for detection and reconstruction of faults which can affect a non-linear model and can be applied directly for fault detection and isolation of actuator faults. The validity of the proposed methodology is illustrated by estimating the state and faults of an automatic steering vehicle.

Keywords: fuzzy modelling; unknown inputs; fuzzy observer; fault detection; fault reconstruction; vehicle dynamics; Lyapunov method; linear matrix inequalities; LMI; disturbances; fault isolation; actuator faults; actuators; automatic steering vehicles.

DOI: 10.1504/IJMIC.2008.019358

International Journal of Modelling, Identification and Control, 2008 Vol.3 No.2, pp.193 - 200

Published online: 08 Jul 2008 *

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