期刊論文
| 學年 | 91 |
|---|---|
| 學期 | 1 |
| 出版（發表）日期 | 2003-01-01 |
| 作品名稱 | A reinforcement discrete neuro-adaptive control for unknown piezoelectric actuator systems with dominant hysteresis |
| 作品名稱（其他語言） | |
| 著者 | 黃志良 |
| 單位 | 淡江大學電機工程學系 |
| 出版者 | |
| 著錄名稱、卷期、頁數 | IEEE Transactions on Neural Networks 14(1), pp. 66-78 |
| 摘要 | The theoretical and experimental studies of a reinforcement discrete neuro-adaptive control for unknown piezoelectric actuator systems with dominant hysteresis are presented. Two separate nonlinear gains, together with an unknown linear dynamical system, construct the nonlinear model (NM) of the piezoelectric actuator systems. A nonlinear inverse control (NIC) according to the learned NM is then designed to compensate the hysteretic phenomenon and to track the reference input without the risk of discontinuous response. Because the uncertainties are dynamic, a recurrent neural network (RNN) with residue compensation is employed to model them in a compact subset. Then, a discrete neuro-adaptive sliding-mode control (DNASMC) is designed to enhance the system performance. The stability of the overall system is verified by Lyapunov stability theory. Comparative experiments for various control schemes are also given to confirm the validity of the proposed control. |
| 關鍵字 | |
| 語言 | en |
| ISSN | |
| 期刊性質 | 國內 |
| 收錄於 | |
| 產學合作 | |
| 通訊作者 | |
| 審稿制度 | 否 |
| 國別 | TWN |
| 公開徵稿 | |
| 出版型式 | ,電子版 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/60811 ) |