標題: | Robust Adaptive Control Scheme Using Hopfield Dynamic Neural Network for Nonlinear Nonaffme Systems |
作者: | Chen, Pin-Cheng Lin, Ping-Zing Wang, Chi-Hsu Lee, Tsu-Tian 電機工程學系 Department of Electrical and Computer Engineering |
關鍵字: | adaptive control;robust control;Hopfield-based dynamic neural network;Lyapunov stability theory |
公開日期: | 2010 |
摘要: | In this paper, we propose a robust adaptive control scheme using Hopfield-based dynamic neural network for uncertain or ill-defined nonlinear nonaffine systems. A Hopfield-based dynamic neural network is used to approximate the unknown plant nonlinearity. The robust adaptive controller is designed to achieve a L-2 tracking performance to stabilize the closed-loop system. The weights of Hop field-based dynamic neural network are on-line tuned by the adaptive laws derived in the sense of Lyapunov, so that the stability of the closed-loop system can be guaranteed, and the tracking error is bounded. The proposed control scheme is applied to control an anti-lock braking system, and the simulation results illustrate the applicability of the proposed control scheme. The designed parsimonious structure of the Hopfield-based dynamic neural network makes the practical implementation of the work in this paper much easier. |
URI: | http://hdl.handle.net/11536/135566 |
ISBN: | 978-3-642-13317-6 |
ISSN: | 0302-9743 |
期刊: | ADVANCES IN NEURAL NETWORKS - ISNN 2010, PT 2, PROCEEDINGS |
Volume: | 6064 |
起始頁: | 497 |
結束頁: | + |
顯示於類別: | 會議論文 |