Title: State estimation for non-linear systems using a decoupled multiple model

Authors: Rodolfo Orjuela, Benoit Marx, Jose Ragot, Didier Maquin

Addresses: Centre de Recherche en Automatique de Nancy, UMR 7039, Nancy-Universite, CNRS 2, Avenue de la Foret de Haye, Vandoeuvre-les-Nancy 54 516, France. ' Centre de Recherche en Automatique de Nancy, UMR 7039, Nancy-Universite, CNRS 2, Avenue de la Foret de Haye, Vandoeuvre-les-Nancy 54 516, France. ' Centre de Recherche en Automatique de Nancy, UMR 7039, Nancy-Universite, CNRS 2, Avenue de la Foret de Haye, Vandoeuvre-les-Nancy 54 516, France. ' Centre de Recherche en Automatique de Nancy, UMR 7039, Nancy-Universite, CNRS 2, Avenue de la Foret de Haye, Vandoeuvre-les-Nancy 54 516, France

Abstract: The multiple model approach is an elegant and a powerful tool for modelling real-world complex processes. In this modelling framework, a judicious combination of a set of submodels makes it possible to describe the behaviour of a non-linear system. Two different structures of multiple models can be distinguished according to whether the submodels share a common state vector (Takagi-Sugeno multiple model) or not (decoupled multiple model). This latter structure is an interesting alternative to the popular Takagi-Sugeno multiple model because different dimensions of submodels can be considered. The decoupled multiple model is nowadays increasingly used to perform the identification and the control of non-linear systems. However, to our knowledge, the state estimation problem of non-linear systems represented by this structure is not thoroughly investigated. The present paper deals with this worthwhile problem.

Keywords: state estimation; nonlinear systems; multiple models; fault detection; modelling; Takagi-Sugeno multiple model; decoupled multiple model.

DOI: 10.1504/IJMIC.2008.021000

International Journal of Modelling, Identification and Control, 2008 Vol.4 No.1, pp.59 - 67

Published online: 30 Oct 2008 *

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