期刊論文
| 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 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/98859 ) |