State and unknown input estimation for nonlinear systems described by Takagi-Sugeno models with unmeasurable premise variables

Author

Ichalal, Dalil ; Marx, Benoît ; Ragot, José ; Maquin, Didier

Author_Institution

Centre de Rech. en Autom. de Nancy (CRAN), Nancy-Univ., Vandoeuvre-les-Nancy, France

fYear

2009

fDate

24-26 June 2009

Firstpage

217

Lastpage

222

Abstract

This paper presents a new method to synthesize observers for continuous time nonlinear systems described by Takagi-Sugeno (TS) model with unmeasurable premise 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).

Keywords

continuous time systems; convergence; fuzzy systems; linear matrix inequalities; nonlinear systems; observers; Takagi-Sugeno model; continuous time nonlinear system; convergence condition; linear matrix inequality; observer synthesization; proportional integral observer; state estimation error; state input estimation; unmeasurable premise variable; Automatic control; Automation; Bismuth; Convergence; Fault detection; Nonlinear control systems; Nonlinear systems; Observers; State estimation; Takagi-Sugeno model;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Automation, 2009. MED '09. 17th Mediterranean Conference on

Conference_Location

Thessaloniki

Print_ISBN

978-1-4244-4684-1

Electronic_ISBN

978-1-4244-4685-8

Type

conf

DOI

10.1109/MED.2009.5164542

Filename

5164542