Neural network-based adaptive robust. control for a class uncertain systems with measurement noise

被引：0
|
作者：
Yang, JY [1 ]
Jia, YM [1 ]
机构：
[1] Beijing Univ Aeronaut & Astronaut, Res Div 7, Beijing 100083, Peoples R China
来源：
2002 IEEE REGION 10 CONFERENCE ON COMPUTERS, COMMUNICATIONS, CONTROL AND POWER ENGINEERING, VOLS I-III, PROCEEDINGS | 2002年
关键词：
measurement noise; robust adaptive control; neural networks; uncertain systems;
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：
In this paper, neural networks'(NNs) and adaptive robust control (ARC) design philosophy are integrated to design performance-oriented control. laws for a class of uncertain systems whose output is corrupted by external disturbances. The derived adaptive-robust control schemes not only guarantee. all the signals are bounded in the closed loop but also make the system preserve certain prescribed properties. The cone-bounded assumption on the uncertain dynamics is removed via neural networks. The feedback information is the state with measurement noise.
引用
收藏
页码：1475 / 1478
页数：4
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