Identification methods for Wiener nonlinear systems based on the least squares and gradient iterations

Author

Wang, Dongqing ; Chu, Yanyun ; Ding, Feng

Author_Institution

Coll. of Autom. Eng., Qingdao Univ., Qingdao, China

fYear

2009

fDate

15-18 Dec. 2009

Firstpage

3632

Lastpage

3636

Abstract

This paper derives a least squares based and a gradient based iterative identification algorithms for Wiener nonlinear systems. These methods separate one bilinear-parameter cost function into two linear-parameter cost functions, estimating directly the parameters of the Wiener systems. The simulation results confirm that the proposed two algorithms are valid and the least squares based iterative algorithm has faster convergence rates than the gradient based iterative algorithm.

Keywords

convergence of numerical methods; gradient methods; identification; least squares approximations; nonlinear systems; Wiener nonlinear systems; Wiener systems; bilinear-parameter cost function; convergence rates; gradient based iterative identification; gradient iterations; least squares based iterative algorithm; Convergence; Cost function; Educational institutions; Iterative algorithms; Iterative methods; Least squares approximation; Least squares methods; Nonlinear dynamical systems; Nonlinear systems; Parameter estimation; Hammerstein models; System modelling; Wiener models; iterative identification; least squares; parameter estimation; recursive identification; stochastic gradient;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC/CCC 2009. Proceedings of the 48th IEEE Conference on

Conference_Location

Shanghai

ISSN

0191-2216

Print_ISBN

978-1-4244-3871-6

Electronic_ISBN

0191-2216

Type

conf

DOI

10.1109/CDC.2009.5399834

Filename

5399834