Self-organized Locally Linear Optimal Tracking Control for Unknown Nonlinear Systems

被引：0
|
作者：
Chen, Yiming [1 ]
Dong, Wenjie [2 ]
Farrell, Jay A. [1 ]
机构：
[1] Univ Calif Riverside, Dept Elect Engn, Riverside, CA 92521 USA
[2] Univ Texas Pan Amer, Dept Elect Engn, Edinburg, TX 78539 USA
来源：
2011 50TH IEEE CONFERENCE ON DECISION AND CONTROL AND EUROPEAN CONTROL CONFERENCE (CDC-ECC) | 2011年
基金：
美国国家科学基金会;
关键词：
NET ROBOT CONTROLLER; ADAPTIVE-CONTROL; NETWORKS;
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 considers optimal full state feedback tracking control of unknown nonlinear systems. To deal with the unknown nonlinearities in the system, small learning regions are assigned online along the system trajectory in a manner dictated by a Lyapunov based self-organization method. In each of these regions, a local affine approximation is developed. A state observer-based approach adapts the approximator parameters. With the aid of this state observer, analytic optimal controllers are proposed by solving corresponding linear quadratic control problems in each learning region. To show the effectiveness of the proposed controllers, a numerical example is included.
引用
收藏
页码：5401 / 5406
页数：6
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