Robust wavelet-based adaptive neural controller design with a fuzzy compensator
學年 98
學期 1
出版（發表）日期 2009-12-01
作品名稱 Robust wavelet-based adaptive neural controller design with a fuzzy compensator
作品名稱（其他語言）
著者 Hsu, Chun-Fei; Cheng, Kuo-Hsiang; Lee, Tsu-Tian
單位 淡江大學電機工程學系
出版者 Amsterdam: Elsevier BV
著錄名稱、卷期、頁數 Neurocomputing 73(1–3), pp.423–431
摘要 In this paper, a robust wavelet-based adaptive neural control (RWANC) with a PI type learning algorithm is proposed. The proposed RWANC system is composed of a wavelet neural controller and a fuzzy compensation controller. The wavelet neural control is utilized to approximate an ideal controller and the fuzzy compensation controller with a fuzzy logic system in it is used to remove the chattering phenomena of conventional sliding-mode control completely. In the RWANC, the learning algorithm is derived based on the Lyapunov function, thus the closed-loop system's stability can be guaranteed. The chaotic system control has become an emerging topic in engineering community since the uncontrolled system displays complex, noisy-like and unpredictable behavior. Therefore, the proposed RWANC approach is applied to a second-order chaotic nonlinear system to investigate the effectiveness. Through the simulation results, the proposed RWANC scheme can achieve favorable tracking performance and the convergence of the tracking error and control parameters can be accelerated by the developed PI adaptation learning algorithm.
關鍵字 Adaptive control; Neural control; Chaotic system; Fuzzy compensation; Wavelet neural network
語言 en
ISSN 0925-2312
期刊性質 國外
收錄於 SCI
產學合作
通訊作者
審稿制度 是
國別 NLD
公開徵稿
出版型式 紙本
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