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

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 H_infin performances with respect to perturbations.