摘要
This paper presents a self-organizing decentralized learning controller using fuzzy control and neurocontrol for large-scale nonlinear systems. A new on-line unsupervised learning method which is based on a performance index of sliding mode control is used to train the fuzzy neural net controller to obtain control actions. To overcome the interactions between the subsystems, a learning algorithm is adopted to modify the control input to improve the system performance. The effectiveness and the performance of the proposed approach are illustrated by the simulation results of a two-inverted pendulum system and a two-link manipulator. The attractive features also include a smaller residual error and robustness against nonlinear interactions.
原文 | 英語 |
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頁面 | 2179-2186 |
頁數 | 8 |
出版狀態 | 已發佈 - 1995 |
事件 | Proceedings of the 1995 IEEE International Conference on Fuzzy Systems. Part 1 (of 5) - Yokohama, Jpn 持續時間: 1995 3月 20 → 1995 3月 24 |
會議
會議 | Proceedings of the 1995 IEEE International Conference on Fuzzy Systems. Part 1 (of 5) |
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城市 | Yokohama, Jpn |
期間 | 1995/03/20 → 1995/03/24 |
ASJC Scopus subject areas
- 軟體
- 理論電腦科學
- 人工智慧
- 應用數學