標題: ADAPTIVELY CONTROLLING NONLINEAR CONTINUOUS-TIME SYSTEMS USING MULTILAYER NEURAL NETWORKS
作者: CHEN, FC
LIU, CC
交大名義發表
電控工程研究所
National Chiao Tung University
Institute of Electrical and Control Engineering
公開日期: 1-Jun-1994
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.
URI: http://dx.doi.org/10.1109/9.293202
http://hdl.handle.net/11536/2465
ISSN: 0018-9286
DOI: 10.1109/9.293202
期刊: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
Volume: 39
Issue: 6
起始頁: 1306
結束頁: 1310
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  1. A1994NU01800028.pdf