State estimation for nonlinear systems using decoupled multiple model

Rodolfo Orjuela (1) , Benoît Marx (1) , José Ragot (1) , Didier Maquin (1)

1 CRAN - Centre de Recherche en Automatique de Nancy

The multiple model approach is an elegant and a powerful tool for mod- elling 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 nonlinear system. The two following 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 orders of submodels can be considered. The decoupled multiple model is nowadays increasingly used to perform the identification and the control of nonlinear systems. However, to our knowledge, the state estimation problem of nonlinear systems represented by this structure is not thoroughly investigated. The present note deals with this worthwhile problem.

Keywords: State estimation; nonlinear systems; multiple model approach; fault detection

Domains: Automatic

Rodolfo Orjuela, Benoît Marx, José Ragot, Didier Maquin. State estimation for nonlinear systems using decoupled multiple model. International Journal of Modelling, Identification and Control, 2008, 4 (1), pp.59-67. ⟨10.1504/IJMIC.2008.021000⟩. ⟨hal-00168647⟩