Browsing by Author "Lin, Ping-Zing"

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Robust Adaptive Control Scheme Using Hopfield Dynamic Neural Network for Nonlinear Nonaffme Systems
(2010)
Chen, Pin-Cheng
;
Lin, Ping-Zing
;
Wang, Chi-Hsu
;
Lee, Tsu-Tian
;
電機工程學系
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.