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基于神经网络的开关磁阻电机转子位置在线检测技术
引用本文:韩锋,边敦新,赵爱丽.基于神经网络的开关磁阻电机转子位置在线检测技术[J].山东理工大学学报,2008,22(5):91-94.
作者姓名:韩锋  边敦新  赵爱丽
作者单位:山东理工大学电气与电子工程学院,山东淄博255049
摘    要:提出了一种基于BP神经网络的开关磁阻电机转子位置在线检测方法。该方法将训练数据实时更新的思想引入到神经网络的输入向量中,利用大量实时更新的电机数据作为神经蹰络的训练样本在网络进行在线训练,修正网络参数,使检测结果不受渐变因素的影响。仿真结果表明,该方法能够准确地检测转子位置,鲁棒性和适应性强。

关 键 词:开关磁阻电机  无位置传感器  神经网络  MATLAB/Simulink

Rotor position estimation of switched reluctance motor based on neural network
HAN Feng,BIAN Dun-xin,ZHAO Ai-li.Rotor position estimation of switched reluctance motor based on neural network[J].Journal of Shandong University of Technology:Science and Technology,2008,22(5):91-94.
Authors:HAN Feng  BIAN Dun-xin  ZHAO Ai-li
Institution:HAN Feng,BIAN Dun-xin,ZHAO Ai-li(School of Electric , Electronic Engineering,Sh,ong University of Technology,Zibo 255049,China)
Abstract:An approach of detecting the rotor position for Switched Reluctance Motors(SRM) based on BP neural network is presented.The method introduces the idea of real-time training data updating into the input vector of neural network.The neural network is trained with the SRM's real-time updating samples to modify the parameters of the neural network.Results of simulation show that this scheme not only can acquire the rotor position timely and exactly but has great robustness and adaptability.
Keywords:MATLAB/Simulink
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