Sliding mode control of nonlinear system based-on neural networks

被引：0

作者：

Lei, HL ^{[1
]}

Zhang, DZ ^{[1
]}

Liu, WH ^{[1
]}

机构：

[1] 106 Air Force Coll Engn, Xian 710038, Peoples R China

来源：

PROCEEDINGS OF THE 3RD WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-5 | 2000年

关键词：

radial based function neural networks; dynamic approximation; variable structure control system with sliding mode; robust; global stability;

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 order to minimize the needing of information from plant, A adaptive sliding mode control scheme for nonlinear plant without any model are proposed in this paper which based On the strong robust of Sliding Mode Control (SMC) and the favorable approximation capability of Base Function neural networks. The global stability of the control system are proved by theory analysis The simulation shows the strong robust and feasibility of the control scheme.

引用

页码：962 / 966

页数：5

共 4 条

[1]

Broomhead D. S., 1988, Complex Systems, V2, P321

[2] DIAGONAL RECURRENT NEURAL NETWORKS FOR DYNAMIC-SYSTEMS CONTROL [J].