Neural network and adaptive algorithm-based fractional order sliding mode controller

被引：7
作者：
Zhang B.-T. [1 ]
Gao F.-R. [1 ]
Yao K. [1 ]
机构：
[1] Guangzhou HKUST Fok Ying Tung Research Institute, Guangzhou, 511458, Guangdong
来源：
Kongzhi Lilun Yu Yingyong/Control Theory and Applications | 2016年 / 33卷 / 10期
关键词：
Adaptive control; Chattering; Fractional order; Neural network; Sliding mode control;
D O I：
10.7641/CTA.2016.50960
中图分类号：
学科分类号：
摘要：
In this paper, a fractional order sliding mode scheme based on neural network self-adapting algorithm is proposed for dealing with the chattering phenomenon existing in conventional sliding mode controller under the existence of parameters variation and external disturbance. Firstly, the fractional order sliding mode control law is designed using equivalent control technology. And a switching control method is obtained to drive the system state to reach the given sliding manifold at any initial condition. Then the neural network and adaptive control algorithm are designed to abate the chattering of sliding mode controller. The stability of control system is analysis by Lyapunov stability theory finally. Experiments demonstrate that the proposed neural network self-adapting based fractional order sliding mode controller not only achieve better control performance than the conventional sliding mode control system, but also is robust with regard to system parameters variation and external disturbance. © 2016, Editorial Department of Control Theory & Applications South China University of Technology. All right reserved.
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页码：1373 / 1377
页数：4
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