Stability of A Class of RNN Controllers for First-order Uncertain Systems

被引：0
|
作者：
Wang, Mengyang [1 ,2 ]
Huang, Yi [1 ,2 ]
机构：
[1] Chinese Acad Sci, Acad Math & Syst Sci, Key Lab Syst & Control, Beijing 100190, Peoples R China
[2] Univ Chinese Acad Sci, Sch Math Sci, Beijing 100049, Peoples R China
来源：
2022 41ST CHINESE CONTROL CONFERENCE (CCC) | 2022年
基金：
国家重点研发计划;
关键词：
uncertain system; stability; robustness; RNN; DYNAMICAL-SYSTEMS; APPROXIMATION;
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：
This paper studies the stability of a class of first-order uncertain systems controlled by a simple recurrent neural network (RNN) controller. The convergence conditions are given. The relationship between the parameters of RNN controller and its robustness is quantitatively analyzed for the linear uncertain system. Simulation examples are provided to verify the analysis results.
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页码：1206 / 1211
页数：6
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