Recursive identification method for a class of Hammerstein-Wiener systems

被引：0

作者：

Yu, Feng ^{[1
]}

Mao, Zhi-Zhong ^{[1
]}

Jia, Ming-Xing ^{[1
]}

Yuan, Ping ^{[1
]}

Yang, Fei-Sheng ^{[2
]}

机构：

[1] School of Information Science and Engineering, Northeastern University, Shenyang 110819, China

[2] School of Automation, Northwestern Polytechnical University, Xi'an 710072, China

来源：

Zidonghua Xuebao/Acta Automatica Sinica | 2014年 / 40卷 / 02期

关键词：

Parameter estimation;

D O I：

10.3724/SP.J.1004.2014.00327

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

A recursive algorithm is presented to identify the Hammerstein-Wiener system with process noise. Based on parameterizing the nonlinear parts of system using polynomial functions strictly, the optimal recursive update formulas are derived in a sense that the expectation of the sum of square of parameter errors is minimized, which avoids the interference of noise. Uniform convergence conditions together with a coefficient setting method, which expands the convergence domain, are given by means of analyzing the algorithm deeply. Simulation results validate the advantage of this algorithm over the two-stage algorithm. Copyright © 2014 Acta Automatica Sinica. All rights reserved.

引用

页码：327 / 335

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