Hierarchical Identification of Hammerstein-Wiener time-delay systems with maximum likelihood and gradient descent algorithm

被引：0
|
作者：
Jiang, Yizhe [1 ]
Song, Weicheng [1 ]
Chu, Jie [1 ]
Li, Junhong [1 ]
机构：
[1] Nantong Univ, Sch Elect Engn, Nantong 226019, 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：
system identification; Hammerstein-Wiener systems; maximum likelihood algorithm; gradient descent algorithm; hierarchical identification;
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：
In this paper, the parameter estimation for Hammerstein-Wiener nonlinear systems with unknown delay is studied. Based on the hierarchical identification principle and two-step identification, the maximum likelihood recursive algorithm is used to identify the parameters of the system, and the gradient descent method is used to identify the time delay. Finally, the algorithm is verified by a numerical example, and the simulation results show that the algorithm has the characteristics of fast convergence speed and high identification accuracy.
引用
收藏
页码：1413 / 1417
页数：5
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