This paper presents a stability method which is based on the stability condition of sliding mode control to derive learning law for neural net controllers (NNC) to ensure the convergence of the training algorithm and the stability of the closed-loop system. The proposed method is an on-line approach of a multilayered neural network which does not required any information about the system dynamics and the lengthy training of the controller might be eliminated by using the proposed approach. The simulation results of a nonlinear system and a two-link manipulator demonstrate that the attractive features of the proposed approach include a smaller residual error and robustness against nonlinear interactions of an interconnected system or external disturbances.
|出版狀態||已發佈 - 1994 十二月 1|
|事件||Proceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7) - Orlando, FL, USA|
持續時間: 1994 六月 27 → 1994 六月 29
|其他||Proceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7)|
|城市||Orlando, FL, USA|
|期間||1994/06/27 → 1994/06/29|
ASJC Scopus subject areas