期刊論文
| 學年 | 89 |
|---|---|
| 學期 | 1 |
| 出版（發表）日期 | 2000-12-01 |
| 作品名稱 | A discrete-time multivariable neuro-adaptive control for nonlinear unknown dynamic systems |
| 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 Systems, Man and Cybern, Part B- Cybernetics 30(6), pp.865-877 |
| 摘要 | First, we assume that the controlled systems contain a nonlinear matrix gain before a linear discrete-time multivariable dynamic system. Then, a forward control based on a nominal system is employed to cancel the system nonlinear matrix gain and track the desired trajectory. A novel recurrent-neural-network (RNN) with a compensation of upper bound of its residue is applied to model the remained uncertainties in a compact subset /spl Omega/. The linearly parameterized connection weight for the function approximation error of the proposed network is also derived. An e-modification updating law with projection for weight matrix is employed to guarantee its boundedness and the stability of network without the requirement of persistent excitation. Then a discrete-time multivariable neuro-adaptive variable structure control is designed to improve the system performances. The semi-global (i.e., for a compact subset /spl Omega/) stability of the overall system is then verified by the Lyapunov stability theory. Finally, simulations are given to demonstrate the usefulness of the proposed controller. |
| 關鍵字 | Nonlinear control systems;Control systems;Nonlinear dynamical systems;Stability;Gain;Trajectory;Recurrent neural networks;Upper bound;Uncertainty;Function approximation |
| 語言 | en_US |
| ISSN | 1083-4419 |
| 期刊性質 | 國外 |
| 收錄於 | |
| 產學合作 | |
| 通訊作者 | |
| 審稿制度 | 否 |
| 國別 | USA |
| 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/987654321/60770 ) |