Design of a CMAC-based smooth adaptive neural controller with a saturation compensator

doi:10.1007/s00521-011-0615-5

淡江大學機構典藏 > 工學院 > 電機工程學系暨研究所 > 期刊論文 > Item 987654321/75379

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题名:	Design of a CMAC-based smooth adaptive neural controller with a saturation compensator
作者:	Yen, Ming-ching;許駿飛;Hsu, Chun-fei;Chung, In-hang
贡献者:	淡江大學電機工程學系暨研究所
关键词:	Chua’s chaotic circuit;DC motor driver;CMAC neural network;Adaptive control;Neural control
日期:	2012-02-01
上传时间:	2012-03-22 14:26:24 (UTC+8)
出版者:	Springer London
摘要:	In the conventional CMAC-based adaptive controller design, a switching compensator is designed to guarantee system stability in the Lyapunov stability sense but the undesirable chattering phenomenon occurs. This paper proposes a CMAC-based smooth adaptive neural control (CSANC) system that is composed of a neural controller and a saturation compensator. The neural controller uses a CMAC neural network to online mimic an ideal controller and the saturation compensator is designed to dispel the approximation error between the ideal controller and neural controller without any chattering phenomena. The parameter adaptive algorithms of the CSANC system are derived in the sense of Lyapunov stability, so the system stability can be guaranteed. Finally, the proposed CSANC system is applied to a Chua’s chaotic circuit and a DC motor driver. Simulation and experimental results show the CSANC system can achieve a favorable tracking performance. It should be emphasized that the development of the proposed CSANC system doesn’t need the knowledge of the system dynamics.
關聯:	Neural Computing and Applications 12(1), pp.35-44
DOI:	10.1007/s00521-011-0615-5
显示于类别:	[電機工程學系暨研究所] 期刊論文

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