Separable gradient estimation algorithm for Hammerstein systems based on decompositions

Author

Feng Ding

Author_Institution

Key Lab. of Adv. Process Control for Light Ind. (Minist. of Educ.), Jiangnan Univ., Wuxi, China

fYear

2012

fDate

27-29 June 2012

Firstpage

3415

Lastpage

3420

Abstract

This paper studies parameter estimation problem of Hammerstein systems by using the gradient search principle. The Hammerstein system is a bilinear-parameter system which is linear about two parameter vectors, respectively. A separable gradient algorithm is developed for estimating the two parameter vectors based on the hierarchical identification principle. The algorithm is simple in principle and easy to implement online. The simulation results test the effectiveness of the proposed algorithm.

Keywords

bilinear systems; gradient methods; nonlinear control systems; parameter estimation; search problems; Hammerstein systems; bilinear-parameter system; decompositions; gradient search principle; hierarchical identification principle; nonlinear systems; parameter estimation problem; parameter vector estimation; separable gradient estimation algorithm; Convergence; Estimation; Iterative methods; Parameter estimation; Signal processing algorithms; Stochastic processes; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference (ACC), 2012

Conference_Location

Montreal, QC

ISSN

0743-1619

Print_ISBN

978-1-4577-1095-7

Electronic_ISBN

0743-1619

Type

conf

DOI

10.1109/ACC.2012.6315354

Filename

6315354