State estimation of nonlinear systems using multiple model approach

Dalil Ichalal (1) , Benoît Marx (1) , José Ragot (1) , Didier Maquin (1)

1 CRAN - Centre de Recherche en Automatique de Nancy

This paper addresses the problem of state estimation of nonlinear systems described by a Takagi-Sugeno multiple model with unmeasurable decision variables. The method is based on the reformulation of the multiple model in an equivalent form. First, the convergence conditions of the state estimation error are established using the Lyapunov method and they are expressed in LMI formulation. Secondly, performances of the observer are enhanced by pole clustering and L2 attenuation of bounded exogenous disturbances. Finally, the method is applied to estimate the state of a link flexible joint robot.

Mots clés: State estimation; nonlinear systems; Takagi-Sugeno models; nonlinear observer

Domaines: Automatique / Robotique

Dalil Ichalal, Benoît Marx, José Ragot, Didier Maquin. State estimation of nonlinear systems using multiple model approach. American Control Conference, ACC 2009, Jun 2009, St Louis, Missouri, United States. pp.4636-4641, ⟨10.1109/ACC.2009.5160393⟩. ⟨hal-00355833⟩