Adaptively controlling nonlinear continuous-time systems using neural networks

Fu-Chuang Chen*, Chen Chung Liu

*此作品的通信作者

研究成果: Conference contribution同行評審

7 引文 斯高帕斯(Scopus)

摘要

Layered neural networks are used in a nonlinear adaptive control problem. The plant is an unknown feedback-linearizable continuous-time system, represented in a state space form. A transformation is made on the plant to decompose the plant into two parts: The first part is modeled and controlled by multilayer neural networks. The second part is unobservable and can not be directly influenced by the control; this part is assumed to be stable. The control law is defined in terms of the neural network model to control the plant to track a reference command. The network parameters are updated on-line according to the tracking error. A theorem is given on the convergence of i) the tracking error and ii) the weight updating. The simulation is performed using Advanced Continuous Simulation Language (ACSL).

原文English
主出版物標題Proceedings of the American Control Conference
發行者Publ by American Automatic Control Council
頁面46-50
頁數5
ISBN(列印)0780302109
DOIs
出版狀態Published - 1 12月 1992
事件Proceedings of the 1992 American Control Conference - Chicago, IL, USA
持續時間: 24 6月 199226 6月 1992

出版系列

名字Proceedings of the American Control Conference
1
ISSN(列印)0743-1619

Conference

ConferenceProceedings of the 1992 American Control Conference
城市Chicago, IL, USA
期間24/06/9226/06/92

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