| 標題：Adaptive dynamic RBF neural controller design for a class of nonlinear systems | |
|---|---|
| 學年 | 100 |
| 學期 | 1 |
| 出版（發表）日期 | 2011/12/01 |
| 作品名稱 | Adaptive dynamic RBF neural controller design for a class of nonlinear systems |
| 作品名稱（其他語言） | |
| 著者 | Hsu, Chun-Fei |
| 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 | Applied Soft Computing 11(8), pp.4607–4613 |
| 摘要 | In this paper, an adaptive DRBF neural control (ADNC) system which is composed of a neural controller and a smooth compensator is proposed. The neural controller utilizes a dynamic radial basis function (DRBF) network to online mimic an ideal controller and the smooth compensator is designed to eliminate the effect of the approximation error between the ideal controller and neural controller. The DRBF network can self-organizing its network structure. All the controller parameters of the proposed ADNC system are online tuned in the Lyapunov sense, thus the stability analytic shows the system output can exponentially converge to a small neighborhood of the trajectory command. Finally, the proposed ADNC system is applied to a chaotic system and a DC motor. Simulation and experimental results verify that a favorable tracking performance and no chattering phenomena can be achieved by the proposed ADNC system. |
| 關鍵字 | Adaptive control; Neural control; Lyapunov stability theorem; DC motor; Chaotic system |
| 語言 | 英文 |
| ISSN | 1568-4946 |
| 期刊性質 | 國外 |
| 收錄於 | SCI |
| 產學合作 | |
| 通訊作者 | Hsu, Chun-Fei |
| 審稿制度 | |
| 國別 | 荷蘭 |
| 公開徵稿 | |
| 出版型式 | 紙本 |
| 相關連結 | |
