RBF神经滑模控制在永磁直线同步电机的应用研究  

Application of RBF Neural Network Sliding Mode Control for PMLSM

作　　者：崔勇 

机构地区：[1]长葛市电力工业公司,河南许昌461000

出　　处：《机电工程技术》2013年第12期31-33,共3页Mechanical & Electrical Engineering Technology

基　　金：河南省科技厅科技攻关计划项目(编号:122102210416);河南省教育厅科学技术研究重点项目(编号:12A470007)

摘　　要：给出了神经网络学习算法和神经滑模控制器的具体设计思路,将滑模控制器的切换函数作为神经网络输入,以滑模控制器为网络输出,从而实现神经网络学习能力和滑模控制自适应切换能力有效结合,将神经滑模控制器应用于永磁直线同步电机伺服系统,通过仿真说明了其良好的跟踪特性和低速平稳性。The learning algorithm of neural networks and neural sliding mode control strategy was proposed which taken switch function as the input of neural network and sliding mode controller as the output,so the self-learning ability of neural network was combined with the adaptive switching ability of sliding mode control. The controller was applied to permanent magnet linear synchronous motor and the simulation result shows its performance of position servo tracking and stability at low speed.

关 键 词：永磁直线同步电机 神经滑模控制 算法 仿真 

分 类 号：TM301.2[电气工程—电机] TP273[自动化与计算机技术—检测技术与自动化装置]