State Estimation for Sensorless Control of BLDC Machine with Particle Filter Algorithm

Yaser Chulaee, H. A. Zarchi, Seyyed Iman Hosseini Sabzevari
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引用次数: 6

Abstract

This paper presents a technique in order to estimate the rotor speed and position of the BLDC machine. In the proposed method, particle filter (PF) is employed to estimate state variables of the machine using measured currents and line voltages. PF is a type of stochastic filters that has wide applications in state estimation of non-linear systems. The main aim of this paper is to utilize particle filter in the sensorless control of BLDC machine and investigate proposed PF algorithm performance. In addition, effective parameters in estimation accuracy and transient response of the filter are discussed. The simulation is performed in MATLAB/SIMULINK environment and results denote that proposed sensorless drive have good accuracy in wide speed range and load torque variation. Also, the algorithm performance is not influenced by the incorrect initial position.
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基于粒子滤波算法的无刷直流电机无传感器控制状态估计
本文提出了一种估算无刷直流电机转子转速和位置的方法。在该方法中,粒子滤波(PF)通过测量电流和线路电压来估计机器的状态变量。PF是一种随机滤波器,在非线性系统的状态估计中有着广泛的应用。本文的主要目的是将粒子滤波应用于无刷直流电机的无传感器控制中,并对所提出的滤波算法的性能进行研究。此外,还讨论了影响滤波器估计精度和瞬态响应的有效参数。在MATLAB/SIMULINK环境下进行了仿真,结果表明所提出的无传感器驱动在较宽的转速范围和负载转矩变化范围内具有良好的精度。算法性能不受初始位置不正确的影响。
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