Global Adaptive Control of A Class of Uncertain Nonlinear Systems Using Neural Networks

被引：0
|
作者：
Chen Pengnian [1 ]
Qin Huashu [2 ]
Sun Mingxuan [3 ]
机构：
[1] China Inst Metrol, Dept Math, Hangzhou 310018, Peoples R China
[2] Chinese Acad Sci, Inst Syst Sci, Beijing 100080, Peoples R China
[3] Zhejiang Univ Technol, Coll Informat Engn, Hangzhou 310014, Zhejiang, Peoples R China
来源：
PROCEEDINGS OF THE 27TH CHINESE CONTROL CONFERENCE, VOL 7 | 2008年
关键词：
Nonlinear system; Adaptive control; Neural network;
D O I：
10.1109/CHICC.2008.4605453
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The paper considers the problem of global adaptive tracking for a class of uncertain nonlinear systems in which the uncertainty is impossible to be parameterized. With the help of the technique of unit partition in differential topology, a result on global approximation of function using neural networks is proved. Based the result, a method of global adaptive neural network control for the uncertain nonlinear system is presented. The method ensures that the tracking error converges to an arbitrarily given small neighborhood of zero. When the tracRed signal is constant, the tracking error converges to zero.
引用
收藏
页码：484 / +
页数：2
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