基于扩展卡尔曼的三相无刷直流电机无传感器矢量控制

A. Ejlali, J. Soleimani
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引用次数: 10

摘要

本文对扩展卡尔曼滤波(EKF)中存在的一些问题进行了主动学习法(ALM)的试错。提出的EKF估计器用于无刷直流电动机的无传感器矢量控制。该估计器使用定子电压和电流来估计状态变量。利用卡尔曼滤波的固有特性,该估计器可以消除电流和电压的滤波。该方案采用电流控制器作为控制策略。仿真结果表明所提出的无传感器无刷直流电机方案具有良好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sensorless vector control of 3-phase BLDC motor using a novel Extended Kalman
This paper execute trial and error method called Active Learning Method (ALM) in Extended Kalman Filter (EKF) that is accompanied by some problems. The proposed EKF estimator used in sensorless vector control of brushless DC motor (BLDCM). This estimator uses stator voltages and currents to estimates state variables. By this estimator, filtering of current and voltage can be eliminated due to inherent properties of kalman filter. In this scheme, current controllers have been used for control strategy. Simulation results show good performance of presented sensorless scheme for BLDCM.
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