Modelling and identification of MIMO nonlinear systems by TS fuzzy application to laboratory quadruple-tank process

Author

El Hajjaji, A. ; Chadli, Mohamed

Author_Institution

Lab. de Modelisation, Univ. de Piucardie Jules Verne, Amiens, France

fYear

2009

fDate

23-26 Aug. 2009

Firstpage

365

Lastpage

370

Abstract

This paper presents a method to identify the parameters of continuous and discrete MIMO Takagi-Sugeno (TS) fuzzy models. The proposed method combines the Levenberg/Marquadt (LM) optimisation algorithm and least squares (LS) method. The LM algorithm is used to estimate the Gaussian membership function parameters whereas the parameters of linear local models is determined using a LS algorithm. To illustrate the effectiveness of the algorithm, an application to a laboratory quadruple-tank process is presented.

Keywords

Gaussian processes; MIMO systems; continuous systems; discrete systems; fuzzy control; least squares approximations; nonlinear control systems; optimisation; parameter estimation; Gaussian membership function parameter estimation; LM optimisation algorithm; LS method; Levenberg-Marquadt optimisation algorithm; MIMO nonlinear systems; TS fuzzy application; continuous MIMO Takagi-Sugeno fuzzy models; discrete MIMO Takagi-Sugeno fuzzy models; laboratory quadruple-tank process; least squares method; linear local models; parameter identification; Analytical models; Equations; Laboratories; MIMO; Mathematical model; Nonlinear systems; Observers;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Conference (ECC), 2009 European

Conference_Location

Budapest

Print_ISBN

978-3-9524173-9-3

Type

conf

Filename

7074429