State and unknown input estimation for nonlinear systems described by Takagi-Sugeno models with unmeasurable premise variables
Résumé
In this paper, a new method to synthesize observers for continuous time nonlinear systems described by Takagi-Sugeno (TS) model with unmeasurable decision variables. First, convergence conditions are established in order to guarantee the convergence of the state estimation error. These conditions are given in Linear Matrix Inequality (LMI) formulation. Secondly, a classical Proportional Integral Observer (PIO) is extended to the considered nonlinear systems in order to estimate the state and the unknown inputs (UI).
Domaines
Automatique / Robotique
Origine : Fichiers produits par l'(les) auteur(s)
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