Adaptive Optimal Output Regulation of Continuous-Time Linear Systems via Internal Model Principle

被引：0
|
作者：
Liu, Yiyang [1 ]
Gao, Weinan [2 ]
机构：
[1] Chinese Acad Sci, Shenyang Inst Automat, Inst Robot & Intelligent Mfg, Shenyang 110016, Liaoning, Peoples R China
[2] Georgia Southern Univ, Allen E Paulson Coll Engn & Comp, Dept Elect & Comp Engn, Statesboro, GA 30460 USA
来源：
2018 9TH IEEE ANNUAL UBIQUITOUS COMPUTING, ELECTRONICS & MOBILE COMMUNICATION CONFERENCE (UEMCON) | 2018年
关键词：
Adaptive control; optimal control; output regulation; internal model principle; reinforcement learning;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
This paper proposes a novel adaptive optimal control approach for output regulation problems of continuous-time linear systems. An internal model is introduced for the sake of controller design. The proposed approach is based on reinforcement learning, which does not rely on the accurate knowledge of system dynamics. The optimal controller for the system incorporating with the internal model is approximated using online input and state data. Simulation results demonstrate the effectiveness of the proposed approach.
引用
收藏
页码：38 / 42
页数：5
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