%0 Journal Article
%A CHEN Gang
%A CHU Ming
%A JIA Qing-xuan
%A SUN Han-xu
%T Compensation Control for Model-Free Dynamic Friction Using Self-Recurrent Wavelet Neural Networks
%D 2013
%R 10.13190/jbupt.201303.16.005
%J Journal of Beijing University of Posts and Telecommunications
%P 16-19
%V 36
%N 3
%X <p>An intelligence control algorithm for friction compensation of low-speed servo system is proposed based on self-recurrent wavelet neural networks. There&rsquo;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.</p>
%U https://journal.bupt.edu.cn/EN/10.13190/jbupt.201303.16.005