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.
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页码：327 / 335
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