Recursive identification of errors-in-variables Wiener systems

被引：14

作者：

Mu, Bi-Qiang ^{[1
]}

Chen, Han-Fu ^{[1
]}

机构：

[1] Chinese Acad Sci, Inst Syst Sci, Acad Math & Syst Sci, Key Lab Syst & Control, Beijing, Peoples R China

来源：

AUTOMATICA | 2013年 / 49卷 / 09期

关键词：

Wiener systems; Errors-in-variables; Stochastic approximation; Recursive estimation; alpha-mixing; Strong consistency;

D O I：

10.1016/j.automatica.2013.06.022

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper considers the recursive identification of errors-in-variables (EIV) Wiener systems composed of a linear dynamic system followed by a static nonlinearity. Both the system input and output are observed with additive noises being ARMA processes with unknown coefficients. By a stochastic approximation in-corporated with the deconvolution kernel functions, the recursive algorithms are proposed for estimating the coefficients of the linear subsystem and for the values of the nonlinear function. All the estimates are proved to converge to the true values with probability one. A simulation example is given to verify the theoretical analysis. (C) 2013 Elsevier Ltd. All rights reserved.

引用

下载

页码：2744 / 2753

页数：10

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