State estimation and diagnosis: a polytopic representation approach
Résumé
Most of the classical methods developed for model-based fault detection and diagnosis are developed for linear models. However, many real-life systems cannot be modeled by linear models. For this purpose, the linear fault-detection methods should be extended using nonlinear approaches. A possible solution that overcomes these limitations is to use linear parameter-varying models. This talk investigates the use of Polytopic Linear Models (PLMs) for the representation, stability analysis, state estimation, control and diagnosis of a class of nonlinear dynamical systems. The PLM structure is introduced as an alternative description of nonlinear dyna- mical systems for the benefit of using classical tools developed in automatic control for linear systems.During this presentation, both theoretical and practical problems will be addressed. Also, difficult situations and future works will be discussed