Deadzone compensation based on constrained RBF neural network

NCUIR > Engineering College > Graduate Institute of Mechanical Engineering > journal & Dissertation > Item 987654321/30834

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/30834

Title:	Deadzone compensation based on constrained RBF neural network
Authors:	Tsai,CH;Chuang,HT
Contributors:	機械工程研究所
Keywords:	LEAST-SQUARES;SYSTEMS;IDENTIFICATION;CONVERGENCE;FEEDFORWARD;ALGORITHM
Date:	2004
Issue Date:	2010-07-06 16:28:25 (UTC+8)
Publisher:	中央大學
Abstract:	In this paper, a modified adaptive neural network for the compensation of deadzone is described, and simulated on a hydraulic positioning system, in which the dynamic model is separated into a series of connection of a nonlinear (deadzone) subsystem and a
Relation:	JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
Appears in Collections:	[Graduate Institute of Mechanical Engineering] journal & Dissertation

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