文章基本信息

标题：INTELLIGENT CONTROL FOR MODEL-FREE ROBOT JOINT WITH DYNAMIC FRICTION USING WAVELET NEURAL NETWORKS
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作者：MING CHU ; JING-ZHOU SONG ; QING-XUAN JIA 等
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2013
卷号：50
期号：1
出版社：Journal of Theoretical and Applied
摘要：In this article, an intelligent compensation control algorithm for low-speed robot joint with dynamic friction was proposed based on self-recurrent wavelet neural networks (SRWNN). It is not necessary to predict the dynamic model parameters, and the high-precision compensation of nonlinear friction is realized by using few neurons and iterations through only position feedback. Lyapunov stability analysis results show the bounded convergence of tracking error and network weights. The servo experimental results from a certain type of robot joint show that the positioning accuracy can be greatly improved by introducing the proposed intelligent algorithm.
关键词：Model-Free; Friction Compensation; Self-Recurrent Wavelet Neural Networks (SRWNN); Compensation Control