Evolutionary computation approach to Wiener model identification

Author

Hatanaka, Toshiharu ; Uosaki, Katsuji ; Koga, Masazumi

Author_Institution

Dept. of Inf. & Knowledge Eng., Tottori Univ., Japan

Volume

1

fYear

2002

Firstpage

914

Lastpage

919

Abstract

A novel approach for nonlinear dynamic system identification is addressed for Wiener models, which are composed of a linear dynamic system part followed by a nonlinear static part. Assuming the nonlinear static part is invertible, we approximate the inverse function by a piecewise linear function, which is estimated by using the evolutionary computation approach such as genetic algorithm (GA) and evolution strategies (ES), while we estimate the linear dynamic system part by the least squares method

Keywords

evolutionary computation; identification; nonlinear dynamical systems; piecewise linear techniques; Wiener model identification; Wiener models; evolution strategies; evolutionary computation; genetic algorithm; linear dynamic system; nonlinear dynamic system identification; piecewise linear function; system identification; Evolutionary computation; Genetics; Least squares approximation; Least squares methods; Nonlinear control systems; Nonlinear dynamical systems; Nonlinear systems; Piecewise linear approximation; Piecewise linear techniques; System identification;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation, 2002. CEC '02. Proceedings of the 2002 Congress on

Conference_Location

Honolulu, HI

Print_ISBN

0-7803-7282-4

Type

conf

DOI

10.1109/CEC.2002.1007047

Filename

1007047