Neural Networks Based Nonlinear H∞ Control for Linear Switched Reluctance Motor

被引：0
|
作者：
Li, Huiyan [1 ]
Liu, Yuliang [1 ]
Wang, Jiang [2 ]
Wong, Y. K. [3 ]
Chan, W. L. [3 ]
机构：
[1] Tianjin Univ Technol & Educ, Sch Elect Engn & Automat, East Liulin,S Dagu Rd, Tianjin 300222, Peoples R China
[2] Tianjin Univ, Sch Elect Engn & Automat, Tianjin 300072, Peoples R China
[3] Hong Kong Polytech Univ, Dept Elect Engn, Kowloon, Peoples R China
来源：
ASCC: 2009 7TH ASIAN CONTROL CONFERENCE, VOLS 1-3 | 2009年
关键词：
PRECISION POSITION CONTROL;
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 is concerned with H-infinity control problems for a class of uncertain nonlinear systems. In the procedure, neural networks (NNs) are used to model the nonlinear functions, H-infinity tracking controller is derived based on Lyapunov function and the notion of dissipativeness. The controller can not only guarantee the stability of the overall control system, but also attenuate the effect of both the external disturbance and NNs approximation error to a prescribed level. Furthermore, theoretical results are applied to a position tracking control of linear switched reluctance motor. Simulation studies are included to demonstrate the effectiveness of the method.
引用
收藏
页码：796 / 801
页数：6
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