Output-feedback adaptive optimal control of interconnected systems based on robust adaptive dynamic programming

被引：184
|
作者：
Gao, Weinan [1 ]
Jiang, Yu [1 ]
Jiang, Zhong-Ping [1 ,2 ]
Chai, Tianyou [2 ]
机构：
[1] NYU, Tandon Sch Engn, Dept Elect & Comp Engn, Brooklyn, NY 11201 USA
[2] Northeastern Univ, State Key Lab Synthet Automat Proc Ind, Shenyang 110819, Liaoning, Peoples R China
来源：
AUTOMATICA | 2016年 / 72卷
基金：
美国国家科学基金会; 中国国家自然科学基金;
关键词：
Approximate/adaptive dynamic programming (ADP); Output-feedback control; Nonlinear dynamic uncertainty; Robust optimal control; NONLINEAR-SYSTEMS; POLICY ITERATION; LINEAR-SYSTEMS; STABILIZATION; DESIGN;
D O I：
10.1016/j.automatica.2016.05.008
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 adaptive and optimal output-feedback problem for continuous-time uncertain systems with nonlinear dynamic uncertainties. Data-driven output-feedback control policies are developed by approximate/adaptive dynamic programming (ADP) based on both policy iteration and value iteration methods. The obtained adaptive and optimal output-feedback controllers differ from the existing literature on the ADP in that they are derived from sampled-data systems theory and are guaranteed to be robust to dynamic uncertainties. A small-gain condition is given under which the overall system is globally asymptotically stable at the origin. An application to power systems is given to test the effectiveness of the proposed approaches. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码：37 / 45
页数：9
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