%0 Journal Article
%T Sliding mode robust tracking control for linear servo system based on RBF neural networks compensation<br>基于RBF神经网络补偿的直线伺服系统滑模鲁棒跟踪控制
%A SUN Yi-biao
%A GUO Qing-ding
%A <br>孙宜标
%A 郭庆鼎
%J 控制理论与应用
%D 2004
%I 
%X Permanent-magnet linear servo system has the merits of high speed, high response, and direct drive etc., but the load disturbance, end effects, nonlinear friction, and the change of system parameters reduce the servo performance of the system. To eliminate the influence of the uncertainties mentioned above for ensuring tracking capability, in this paper a robust tracking control strategy is proposed, combining the variable structure control (VSC) with the radial basis function neuron network (RBFNN). The VSC has the merits of high response and the invariability to uncertainties, but its "chattering" phenomenon negatively affects the placidity and positioning precision of the linear servo system. An RBFNN is applied to model the uncertainties caused by end effects, parameter variations, friction, and external load etc., and an objective function with dead zone is introduced to shorten the learning process. The compensation control based on RBFNN attenuates the chattering level of the control input and improves the static precision of the system. The simulation results show that this control scheme not only has a strong robustness to uncertainties of the linear system, but also has a good tracking performance. In fact, the control greatly improves the robust tracking precision of the direct drive linear servo system.
%K permanent-magnet linear synchronization motor
%K direct-drive
%K end effects
%K sliding mode variable structure control
%K chattering
%K radial basis function neuron network<br>永磁直线同步电机
%K 直接驱动
%K 端部效应
%K 滑模变结构控制
%K 抖振
%K 径向基函数神经网络
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=6B0FEB49F6BE88AA&yid=D0E58B75BFD8E51C&vid=659D3B06EBF534A7&iid=0B39A22176CE99FB&sid=10828928EB89AD8E&eid=80BD0A2EF8664214&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=3&reference_num=7