电工技术学报2018，Vol.33Issue(5)：973-979,7.DOI:10.19595/j.cnki.1000-6753.tces.170881
基于Elman神经网络的永磁直线同步电机互补滑模控制
Complementary Sliding Mode Control for Permanent Magnet Linear Synchronous Motor Based on Elman Neural Network
摘要
Abstract
For the problem that the permanent magnet linear synchronous motor (PMLSM) is vulnerable to the influence of nonlinear factors such as system parameters change and external disturbance and so on, the control performance of the servo system is reduced. A complementary sliding mode control method based on Elman neural network is proposed. The complementary sliding mode control is based on the conventional sliding mode control, adding a generalized error sliding surface, which can not only reduce the system state to the sliding surface time, but also guarantee the system tracking accuracy. However, in practical applications, the switching gain and the value of boundary layer thickness are difficult to select in the complementary sliding mode control. In order to accurately estimate the value of the uncertain factors in the system and to weaken the chattering phenomenon of the sliding mode control, the Elman neural network estimator is used to estimate the value of the uncertain factors, instead of the switching control in the sliding mode control, the influence of uncertain factors on the servo control system is reduced, and the robustness of the system is further improved. The experimental results show that the complementary sliding mode control based on Elman neural network not only improves the position tracking performance of the system, but also increases the robust performance of the system compared with the complementary sliding mode control.关键词
永磁直线同步电机/互补滑模控制/Elman神经网络/抖振现象Key words
Permanent magnet linear synchronous motor/complementary sliding mode control/Elman neural network/chatting phenomenon分类
信息技术与安全科学引用本文复制引用
赵希梅,金鸿雁..基于Elman神经网络的永磁直线同步电机互补滑模控制[J].电工技术学报,2018,33(5):973-979,7.基金项目
辽宁省自然科学基金计划重点项目(20170540677)和辽宁省教育厅科学技术研究项目(LQGD2017025)资助. （20170540677）
