%0 Journal Article
%T Neural-network-based adaptive sliding mode control for PMSM<br>基于神经网络的PMSM自适应滑模控制
%A LI Hong-ru
%A GU Shu-sheng
%A <br>李鸿儒
%A 顾树生
%J 控制理论与应用
%D 2005
%I 
%X With the combination of the merits of sliding-mode control and neural network,a neural-network-based adaptive sliding-mode control scheme for permanent magnet synchronous motor (PMSM) is proposed.First,a sliding-mode controller with an integral-operation switching surface is designed.Then a recurrent neural network is used to estimate the upper bound of uncertainties in real-time,which include parameter variations and external load disturbance,such that the control effort of the sliding-mode controller is reduced.Furthermore,in order to reduce the chattering phenomenon,the sign function in sliding-mode controller is replaced by the saturation function.Theoretical analysis and experiment simulation results show that the proposed strategy has high-performance dynamic characteristics and stronger robustness.
%K permanent magnet synchronous motor (PMSM)
%K sliding-mode control
%K neural network
%K chattering<br>永磁同步电机
%K 滑模变结构控制
%K 神经网络
%K 抖振
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=8816FDA797B16999&yid=2DD7160C83D0ACED&vid=BC12EA701C895178&iid=38B194292C032A66&sid=FCACFF68346F8D4F&eid=1A033C02510EFBE6&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=5&reference_num=12