Recursive parameter estimation for Hammerstein-Wiener systems using modified EKF algorithm

被引:44
作者
Yu, Feng [1 ]
Mao, Zhizhong [1 ]
Yuan, Ping [1 ]
He, Dakuo [1 ]
Jia, Mingxing [1 ]
机构
[1] Northeastern Univ, Dept Control Theory & Control Engn, 11,Lane 3,WenHua Rd, Shenyang, Liaoning, Peoples R China
关键词
Hammerstein-Wiener system; Recursive parameter estimation; Extended Kalman filter algorithm; Multiple input single output; Uniform convergence; IDENTIFICATION; MODEL; OBSERVER;
D O I
10.1016/j.isatra.2017.05.012
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 focuses on the recursive parameter estimation for the single input single output Hammerstein-Wiener system model, and the study is then extended to a rarely mentioned multiple input single output Hammerstein-Wiener system. Inspired by the extended Kalman filter algorithm, two basic recursive algorithms are derived from the first and the second order Taylor approximation. Based on the form of the first order approximation algorithm, a modified algorithm with larger parameter convergence domain is proposed to cope with the problem of small parameter convergence domain of the first order one and the application limit of the second order one. The validity of the modification on the expansion of convergence domain is shown from the convergence analysis and is demonstrated with two simulation cases. (C) 2017 ISA. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:104 / 115
页数:12
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