Design of adaptive neural net controller

研究成果: 書貢獻/報告類型會議貢獻

3 引文 斯高帕斯(Scopus)

摘要

This paper presents an adaptive neural net controller for controlling given plants which are unknown. In the neural net structure, a two-layered network is used to emulate the unknown plant dynamics, and another two-layer neural network, which is the inverse of the estimator, is used to generate the control action on-line. A modified Widrow-Hoff delta rule is adopted as a learning algorithm to minimize the error between the real plant response and the output of the estimator. An effective learning method which is based on sliding motions is provided to tune the control action to improve the system performance and convergence. The major advantage of the proposed approach is that the lengthy training of the controller might be eliminated. The effectiveness of the proposed approach is illustrated through simulations of controlling a unstable plant and a normalized motor model with noise disturbances.

原文英語
主出版物標題International IEEE/IAS Conference on Industrial Automation and Control: Emerging Technologies, Proceedings
發行者IEEE
頁面335-341
頁數7
出版狀態已發佈 - 1995
事件Proceedings of the 1995 International IEEE/IAS Conference on Industrial Automation and Control: Emerging Technologies - Taipei, Taiwan
持續時間: 1995 五月 221995 五月 27

其他

其他Proceedings of the 1995 International IEEE/IAS Conference on Industrial Automation and Control: Emerging Technologies
城市Taipei, Taiwan
期間95/5/2295/5/27

ASJC Scopus subject areas

  • Engineering(all)

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  • 引用此

    Yeh, Z. M. (1995). Design of adaptive neural net controller. 於 International IEEE/IAS Conference on Industrial Automation and Control: Emerging Technologies, Proceedings (頁 335-341). IEEE.