基于递归模糊神经网络的PMLSM伺服控制  

Position Servo Control for Permanent Magnet Linear Synchronous Motor Based on Recurrent Fuzzy Neural Network

作　　者：吴雪芬[1] 

机构地区：[1]常州工学院电子信息与电气工程学院,常州213002

出　　处：《电气自动化》2010年第1期41-43,共3页Electrical Automation

摘　　要：为了增强永磁直线同步电机(PMLSM)直接驱动系统的鲁棒性,改善系统受突加扰动情况下的性能,结合递归神经网络与模糊控制的优点,设计了基于递归模糊神经网络补偿器的PMLSM位置控制器。仿真结果表明,所设计的系统能实现对位置阶跃指令的快速无超调跟踪和稳态无静差,具有很强的鲁棒性,能够满足高精度、微进给永磁直线同步电机伺服驱动系统的要求。In order to enhance the robustness of permanent magnet linear synchronous motor （PMLSM） direct drive system, and improve its performance under suddenly disturbance, the recurrent fuzzy neural network compensator is desiged combining the merits of recurrent neural network and fuzzy control. Simulating results show that the designed method has strong robustness and strong tracking rapidity without overshot and zero steady-state error, and can satisfy requiIments of the high precision and micro-feeding PMLSM drive system.

关 键 词：永磁同步直线电机 递归 模糊 神经网络 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]