A Recursive Identification Algorithm for Wiener Nonlinear Systems with Linear State-Space Subsystem

被引：1
作者：
Junhong Li
Wei Xing Zheng
Juping Gu
Liang Hua
机构：
[1] Nantong University,School of Electrical Engineering
[2] Western Sydney University,School of Computing, Engineering and Mathematics
来源：
Circuits, Systems, and Signal Processing | 2018年 / 37卷
关键词：
Wiener nonlinear systems; System identification; Parameter estimation; Maximum likelihood; State-space model; Recursive identification;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This paper addresses the problem of recursive identification of Wiener nonlinear systems whose linear subsystems are observable state-space models. The maximum likelihood principle and the recursive identification technique are employed to develop a recursive maximum likelihood identification algorithm which estimates the unknown parameters and the system states interactively. In comparison with the developed recursive maximum likelihood algorithm, a recursive generalized least squares algorithm is also proposed for identification of such Wiener systems. The performance of the developed algorithms is validated by two illustrative examples.
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页码：2374 / 2393
页数：19
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