Compensation control for model-free dynamic friction using self-recurrent wavelet neural networks

被引：0
|
作者：
机构：
[1] Automation School, Beijing University of Posts and Telecommunications
来源：
Chu, M. (chuming_bupt@bupt.edu.cn) | 1600年 / Beijing University of Posts and Telecommunications卷 / 36期
关键词：
Friction compensation; Intelligence control; Model-free; Self-recurrent wavelet neural networks;
D O I：
10.13190/jbupt.201303.16.005
中图分类号：
学科分类号：
摘要：
An intelligence control algorithm for friction compensation of low-speed servo system is proposed based on self-recurrent wavelet neural networks. There's of no necessary to predict the system 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 shows the bounded convergence of tracking error and network weights. Also the servo experiments from a robot joint show that the servo positioning accuracy can be greatly improved by introducing the proposed compensation algorithm.
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页码：16 / 19
页数：3
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