基于人工神经网络的永磁无刷直流电动机转矩脉动控制与调速

N. Kishore, Surbhi Singh
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引用次数: 8

摘要

提出了一种基于人工神经网络(ANN)的永磁无刷直流电动机低转矩脉动控制方法。传统的无刷直流电动机在电磁转矩中产生较大的波动,并且不能直接控制。由于高转矩波动引起的振动,电机可能导致部件损失以及轴承故障。传统的无刷直流电动机驱动器(BLDCMD)的主要缺点是在瞬态和动态工况下转矩波动大,转速降低。使用所提出的控制技术可以减少这一缺点。在该控制技术中,无刷直流电机的速度由PI控制器调节,转矩脉动由人工神经网络减小。在MATLAB Simulink中对传统的无刷直流电机进行了完整的仿真。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Torque ripples control and speed regulation of Permanent magnet Brushless dc Motor Drive using Artificial Neural Network
This paper presents a torque control of Permanent magnet Brushless DC (PMBLDC) Motor Drive using Artificial Neural Network (ANN) for low torque ripples. Conventional BLDC Motor produces high ripples in electromagnetic torque and it is not directly controlled. The motor may lead to component loss as well as bearing failure due to vibrations caused by high torque ripples. The main drawback with the conventional Brushless dc motor drives (BLDCMD) is high torque ripples and the speed of BLDCMD is reduced under transient and dynamic state of operating condition. This drawback is reduced using with the proposed control technique. In this proposed control technique the speed of the BLDCMD is regulated by the PI controller and the torque ripple is reduced by the ANN. Complete simulation of the conventional BLDCMD is done in MATLAB Simulink.
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