State Estimation via Observers with Unknown Inputs: Application to a Particular Class of Uncertain Takagi-Sugeno Systems

Wafa Jamel, Atef Khedher, Nasreddine Bouguila, Kamel Ben Othman

Abstract

This paper deals with the design of a multiple observer allowing estimating the state vector of a nonlinear system described by a Takagi-Sugeno multiple model subject to modelling and input uncertainties which are considered as unknown inputs. The main contribution of the paper is the conception of a multiple observer based on the elimination of these unknown inputs. Convergence conditions are established in order to guarantee the convergence of the state estimation error. These conditions are expressed in Linear Matrix Inequality (LMI) formulation. An example of simulation is given to illustrate the proposed method.

Keywords

Multiple model approach, Takagi-Sugeno models, multiple observer, unknown inputs, state estimate, modelling and input uncertainties.

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