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基于BP神经网络的中低速磁浮列车速度估计算法
引用本文:刘少克,张文雅.基于BP神经网络的中低速磁浮列车速度估计算法[J].湖南工业大学学报,2007,21(5):55-57.
作者姓名:刘少克  张文雅
作者单位:1. 国防科技大学,湖南,长沙,410073
2. 63999部队,北京,100094
摘    要:提出结合磁浮列车牵引用直线感应电机特点,利用BP神经网络算法,实现对磁浮列车的运行速度观测。通过对一直线感应电机动态模拟实验台进行研究表明,理论估算和实测速度相吻合,初步表明该方法是可行的。该方法的实现,节省了现有磁浮列车速度检测系统昂贵的成本,减少了系统硬件设备的复杂性,提高了整个磁浮列车系统工作的可靠性。

关 键 词:磁浮列车  直线感应电机  神经网络  无速度传感器
文章编号:1673-9833(2007)05-0055-03
收稿时间:2007-08-12

On Estimation Algorithm for Low Speed Maglev Train Based on BP Neural Network
Liu Shaoke and Zhang Wenya.On Estimation Algorithm for Low Speed Maglev Train Based on BP Neural Network[J].Journal of Hnnnan University of Technology,2007,21(5):55-57.
Authors:Liu Shaoke and Zhang Wenya
Affiliation:1. National University of Defense Technology, Changsha410073, China; 2. Army 63999, Peking 100094, China
Abstract:Maglev train is a new vehicle without support wheel and its movement speed is gained by means of a special measure equipment.By using BP neural network arithmetic,the maglev train speed can be estimated by means of combining characteristics of its traction linear induction motor.Based on a dynamic simulation experiment,real speed measure result is near to theory calculation.This shows the method is feasible.In view of the method,it can economize expensive cost for speed measurement of maglev train,reduce system equipment complexity,and also advance work reliability of entire train system.
Keywords:maglev train  linear induction motor  neural network  speed sensorless
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