Adaptive intelligent tracking control using RCMAC for uncertain nonlinear chaotic systems

被引：0
|
作者：
Peng, Ya-Fu [1 ]
Lin, Ming-Hung [2 ]
Lin, Chih-Min [2 ]
机构：
[1] Ching Yun Univ, Dept Elect Engn, Chungli 320, Taiwan
[2] Yuan Ze Univ, Dept Elect Engn, Chungli 320, Taiwan
来源：
IMECS 2007: INTERNATIONAL MULTICONFERENCE OF ENGINEERS AND COMPUTER SCIENTISTS, VOLS I AND II | 2007年
关键词：
adaptive control; recurrent cerebellar model; articulation controller; sliding mode control;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, an adaptive intelligent tracking control (AITC) scheme using an adaptive recurrent cerebellar model articulation controller (RCMAC) is developed for a class of uncertain nonlinear chaotic systems. This AITC system offers a design approach to drive the state trajectory to track a desired trajectory, and it is comprised of an adaptive RCMAC and a robust controller. The adaptive RCMAC is used to mimic an ideal sliding mode control, and a robust controller is designed to recover the residual approximation error for guaranteeing the stable characteristic. The all adaptation laws of the AITC system are derived based on the Lyapunov stability analysis, so that the stability of the system can be guaranteed. Finally, the proposed AITC system is applied to control a Van der Pol oscillator and a Genesio chaotic system. The effectiveness of the proposed control scheme is verified by some simulation results with unknown system dynamics and existence of external disturbance.
引用
收藏
页码：232 / +
页数：3
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