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A novel position sensorless driving system of brushless DC motors based on neural networks

机译:基于神经网络的无刷直流电机的新型位置无传感器驱动系统

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In this paper, a position sensorless driving method of brushless DC motors (BLDCMs) using neural networks has been proposed. Considering the nonlinear characteristics of BLDCM and the parameter errors in the modeling, neural networks can be considered as a powerful tool. Thus, we introduce a neural network to estimate the electromotive force (EMF). Instead of directly estimating the position information from EMF, we propose a new method to estimating the position errors and then using approximate algorithm to obtain the rotor position. The results of simulation and experiment using offline trained neural networks show that the BLDCM is controlled well under load conditions. The proposed method can be believed have high possibility in practical applications.
机译:本文已经提出了使用神经网络的无刷直流电动机(BLDCMS)的位置无传感器驱动方法。考虑到BLDCM的非线性特征和建模中的参数误差,神经网络可以被视为强大的工具。因此,我们介绍了神经网络来估计电动势(EMF)。我们提出了一种新的方法来估计位置误差,而不是直接估计来自EMF的位置信息,而不是使用近似算法来获得转子位置。使用离线训练的神经网络进行仿真和实验结果表明,BLDCM在负载条件下控制得很好。可以相信所提出的方法在实际应用中具有很高的可能性。

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