Gradient-Based Recursive Identification Methods for Input Nonlinear Equation Error Closed-Loop Systems

被引：0
作者：
Bingbing Shen
Feng Ding
Ahmed Alsaedi
Tasawar Hayat
机构：
[1] Jiangnan University,Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), School of Internet of Things Engineering
[2] King Abdulaziz University,Department of Mathematics, Nonlinear Analysis and Applied Mathematics (NAAM) Research Group
[3] Quaid-I-Azam University,Department of Mathematics
来源：
Circuits, Systems, and Signal Processing | 2017年 / 36卷
关键词：
Parameter estimation; Stochastic gradient; Multi-innovation; Hierarchical identification; Nonlinear system; Closed-loop system;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
The identification problem of closed-loop or feedback nonlinear systems is a hot topic. Based on the hierarchical identification principle, this paper presents a hierarchical stochastic gradient algorithm and a hierarchical multi-innovation stochastic gradient algorithm for feedback nonlinear systems. The simulation results show that the hierarchical multi-innovation stochastic gradient can more effectively estimate the parameters of the feedback nonlinear systems than the hierarchical stochastic gradient algorithm.
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页码：2166 / 2183
页数：17
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