Adaptive PI Hermite neural control for MIMO uncertain nonlinear systems

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 987654321/91651

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题名:	Adaptive PI Hermite neural control for MIMO uncertain nonlinear systems
作者:	Hsu, Chun-Fei
贡献者:	淡江大學電機工程學系
关键词:	Hermite neural network;Adaptive control;Neural control;Pendulum;Robotic manipulator
日期:	2013-05-01
上传时间:	2013-07-23 21:46:57 (UTC+8)
出版者:	Amsterdam: Elsevier BV
摘要:	This paper presents an adaptive PI Hermite neural control (APIHNC) system for multi-input multi-output (MIMO) uncertain nonlinear systems. The proposed APIHNC system is composed of a neural controller and a robust compensator. The neural controller uses a three-layer Hermite neural network (HNN) to online mimic an ideal controller and the robust compensator is designed to eliminate the effect of the approximation error introduced by the neural controller upon the system stability in the Lyapunov sense. Moreover, a proportional–integral learning algorithm is derived to speed up the convergence of the tracking error. Finally, the proposed APIHNC system is applied to an inverted double pendulums and a two-link robotic manipulator. Simulation results verify that the proposed APIHNC system can achieve high-precision tracking performance. It should be emphasized that the proposed APIHNC system is clearly and easily used for real-time applications.
關聯:	Applied Soft Computing 13(5), pp.2569–2576
DOI:	10.1016/j.asoc.2012.11.029
显示于类别:	[電機工程學系暨研究所] 期刊論文

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