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Estimating the state and the unknown inputs of nonlinear systems using a multiple model approach

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4 Author(s)
Rodolfo Orjuela ; Centre de Recherche en Automatique de Nancy (CRAN), Nancy-Université, CNRS, 2 avenue de la Forêt de Haye F-54516, Vandoeuvre-lès-Nancy, France ; Benoit Marx ; Jose Ragot ; Didier Maquin

This paper addresses both state and unknown input estimation problem of nonlinear systems modelled with the help of a particular class of multiple models, known as decoupled multiple model. The simultaneous estimation of the state and the unknown inputs is achieved using a proportional-integral observer that is well known by its robustness properties. The proposed observer allows the use of submodels with different dimensions and this fact offers potential applications in the multiple model framework. The LMI framework is used in order to provide sufficient conditions for ensuring exponential convergence of the estimation error and robust Hinfin performances with respect to perturbations.

Published in:

Control and Automation, 2008 16th Mediterranean Conference on

Date of Conference:

25-27 June 2008