电工技术学报2016，Vol.31Issue(23)：9-14,6.
永磁直线同步电机的智能互补滑模控制
Intelligent Complementary Sliding Mode Control for Permanent Magnet Linear Synchronous Motor
摘要
Abstract
Intelligent complementary sliding mode control(ICSMC)based on radial basis function(RBF)neural network is proposed for position tracking precision in permanent magnet linear synchronous motor(PMLSM)servo system.Firstly,PMLSM dynamic equation which contains uncertainty factors such as the end effect,parameter variations,external disturbances and nonlinear friction is established.Then,complementary sliding mode controller is designed by adopting the combination of the generalized sliding surface and the complementary sliding surface in order to reduce the system tracking error,improve response speed and weak the chattering.RBF neural network is employed to estimate the system uncertainty directly.Moreover,RBF network parameters which are trained online can improve the system dynamic performance and robustness.Furthermore,the Lyapunov theorem is used to guarantee the close-loop system stability.By analyzing the system experiment results, it is proved that the proposed control method effectively reduces the system tracking error, and makes the system have good dynamic performance and robust performance.关键词
永磁直线同步电机/互补滑模控制/径向基函数神经网络Key words
Permanent magnet linear synchronous motor/complementary sliding mode control/radial basis function neural network分类
信息技术与安全科学引用本文复制引用
赵希梅,赵久威..永磁直线同步电机的智能互补滑模控制[J].电工技术学报,2016,31(23):9-14,6.基金项目
国家自然科学基金项目(51175349)、辽宁省教育厅科学技术研究项目(L2013060)和沈阳市科技计划项目(F12-277-1-70)资助. （51175349）
