Stochastic approximation in nonparametric identification of Hammerstein systems

Author

Greblicki, Wlodzimierz

Author_Institution

Inst. of Eng. Cybern., Wroclaw Univ., Poland

Volume

47

Issue

11

fYear

2002

fDate

11/1/2002 12:00:00 AM

Firstpage

1800

Lastpage

1810

Abstract

Derived from the idea of stochastic approximation, recursive algorithms to identify a Hammerstein system are presented. Two of them recover the characteristic of the nonlinear memoryless subsystem, while the third one estimates the impulse response of the linear dynamic part. The a priori information about both subsystems is nonparametric. Consistency in quadratic mean is shown, and the convergence rate is examined. Results of numerical simulation are also presented.

Keywords

nonlinear control systems; recursive estimation; stochastic processes; transient response; Hammerstein systems; a priori information; convergence rate; impulse response; nonlinear memoryless subsystem; nonparametric identification; numerical simulation; quadratic mean; recursive algorithms; recursive identification; stochastic approximation; Approximation algorithms; Convergence; Helium; Interconnected systems; Nonlinear dynamical systems; Numerical simulation; Polynomials; Signal processing; Stochastic systems; System identification;

fLanguage

English

Journal_Title

Automatic Control, IEEE Transactions on

Publisher

ieee

ISSN

0018-9286

Type

jour

DOI

10.1109/TAC.2002.804483

Filename

1047007