Adaptively Controlling Nonlinear Continuous-Time Systems Using Multilayer Neural Networks

Fu-Chuang Chen, Chen Chung Liu

研究成果: Article同行評審

255 引文 斯高帕斯(Scopus)

摘要

Multilayer neural networks are used in a nonlinear adaptive control problem. The plant is an unknown feedback-linearizable continuous-time system. The control law is defined in terms of the neural network models of system nonlinearities to control the plant to track a reference command. The network parameters are updated on-line according to a gradient learning rule with dead zone. A local convergence result is provided, which says that if the initial parameter errors are small enough, then the tracking error will converge to a bounded area. Simulations are designed to demonstrate various aspects of theoretical results.

原文English
頁(從 - 到)1306-1310
頁數5
期刊IEEE Transactions on Automatic Control
39
發行號6
DOIs
出版狀態Published - 6月 1994

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