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.
引用
收藏
页码:2166 / 2183
页数:17
相关论文
共 109 条
[71]  
Wang YJ(undefined)undefined undefined undefined undefined-undefined
[72]  
Ding F(undefined)undefined undefined undefined undefined-undefined
[73]  
Wang YJ(undefined)undefined undefined undefined undefined-undefined
[74]  
Ding F(undefined)undefined undefined undefined undefined-undefined
[75]  
Wang YJ(undefined)undefined undefined undefined undefined-undefined
[76]  
Ding F(undefined)undefined undefined undefined undefined-undefined
[77]  
Wang TZ(undefined)undefined undefined undefined undefined-undefined
[78]  
Qi J(undefined)undefined undefined undefined undefined-undefined
[79]  
Xu H(undefined)undefined undefined undefined undefined-undefined
[80]  
Wang J(undefined)undefined undefined undefined undefined-undefined