基于人工神经网络的凸极无刷直流电机转子初始位置估计

T. Senjyu, N. Urasaki, K. Uezato
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引用次数: 0

摘要

提出了一种凸极无刷直流电动机转子位置的初始估计方法。采用人工神经网络(ANN)作为静止状态下无刷直流电机的估计器。人工神经网络可以表达无刷直流电机的电压和电流之间的关系。仅利用人工神经网络的电流信号就可以估计转子的初始位置。该方法具有测量噪声抗扰性好、对机器参数不敏感等优点。计算机仿真结果验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Initial rotor position estimation of salient-pole brushless DC motors by artificial neural network
This paper presents an initial rotor position estimation method for salient-pole brushless DC motors (BLDCMs). An artificial neural network (ANN) is employed as an estimator of BLDCM at standstill. The ANN can express the relationship between the voltage and current of BLDCMs. The initial rotor position can be estimated by using only the current-signals from the ANN. The proposed method has the advantages of measurement noise immunity as well as no sensitivity to machine parameters. Computer simulation results verify the usefulness of the proposed method.
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