Errors-In-Variables Hammerstein-Wiener model identification

被引：0
|
作者：
Su, Hao [1 ]
Hou, Jie [1 ]
机构：
[1] Chongqing Univ Posts & Telecommun, Coll Automat, Chongqing 400065, Peoples R China
来源：
2022 41ST CHINESE CONTROL CONFERENCE (CCC) | 2022年
基金：
中国国家自然科学基金;
关键词：
parameter identification; EIV Hammerstein-Wiener systems; Bias-Correction Least Squares(BCLS) algorithm; NONLINEAR-SYSTEMS; SUBSPACE IDENTIFICATION; ALGORITHM;
D O I：
暂无
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 concerns the parameter identification problem for Errors-In-Variables(EIV) Hammerstein-Wiener systems using available noisy measurements. Based on the least squares method and consistency, a Bias-Correction Least Squares(BCLS) algorithm is proposed to estimate EIV Hammerstein-Wiener systems. The major contribution of this study is to derive the estimation bias of the least squares method and to recursively represent the monomial of noiseless measurements as available measurements. The effectiveness of the algorithm is demonstrated through the identification of simulation example.
引用
收藏
页码：1378 / 1383
页数：6
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