Adaptive neuro-fuzzy identification method of Hammerstein model

Author

Jia, Li ; Chiu, Min-Sen ; Ge, Shuzhi Sam ; Wang, Zhuping

Author_Institution

Dept. of Chem. & Biomolecular Eng., Singapore Nat. Univ.

Volume

2

fYear

2004

fDate

2004

Firstpage

937

Lastpage

942

Abstract

In this paper, adaptive neuro-fuzzy identification is investigated for the Hammerstein model, which consists of the cascade structure of a static nonlinearity followed by a linear dynamic part. Utilizing the approximation ability of neuro-fuzzy for the nonlinear static function, there is no need for prior knowledge and restriction on static nonlinear function. Furthermore, an adaptive algorithm designed by Lyapunov stability theory is proposed to obtain the neuro-fuzzy Hammerstein model. Example is used to illustrate the performance and applicability of the proposed neuro-fuzzy Hammerstein model

Keywords

Lyapunov methods; adaptive systems; fuzzy neural nets; identification; nonlinear functions; Lyapunov stability theory; adaptive algorithm; adaptive neuro-fuzzy identification; cascade structure; neuro-fuzzy Hammerstein model; neuro-fuzzy approximation ability; nonlinear static function; static nonlinear function; static nonlinearity; Adaptive algorithm; Algorithm design and analysis; Biological system modeling; Chemical engineering; Fuzzy neural networks; Lyapunov method; Neural networks; Nonlinear dynamical systems; Polynomials; Water heating;

fLanguage

English

Publisher

ieee

Conference_Titel

Cybernetics and Intelligent Systems, 2004 IEEE Conference on

Conference_Location

Singapore

Print_ISBN

0-7803-8643-4

Type

conf

DOI

10.1109/ICCIS.2004.1460714

Filename

1460714