Convergence of the iterative Hammerstein system identification algorithm

Author

Bai, Er-Wei ; Li, Duan

Author_Institution

Dept. of Electr. & Comput. Eng., Univ. of Iowa, Iowa City, IA, USA

Volume

49

Issue

11

fYear

2004

Firstpage

1929

Lastpage

1940

Abstract

The convergence of the iterative identification algorithm for the Hammerstein system has been an open problem for a long time. In this paper, a detailed study is carried out and various convergence properties of the iterative algorithm are derived. It is shown that the iterative algorithm with normalization is convergent in general. Moreover, it is shown that convergence takes place in one step (two least squares iterations) for finite-impulse response Hammerstein models with i.i.d. inputs.

Keywords

cascade systems; convergence of numerical methods; identification; iterative methods; least mean squares methods; nonlinear control systems; Hammerstein system; finite impulse response; iterative identification algorithm convergence; least square iterations; nonlinear systems; Convergence; Frequency domain analysis; Helium; Iterative algorithms; Least squares methods; Nonlinear dynamical systems; Nonlinear systems; Parameter estimation; Stochastic processes; System identification; 65; Hammerstein systems; nonlinear systems; parameter estimation; system identification;

fLanguage

English

Journal_Title

Automatic Control, IEEE Transactions on

Publisher

ieee

ISSN

0018-9286

Type

jour

DOI

10.1109/TAC.2004.837592

Filename

1356113