Identification of Transfer Function Parameters of Brushless DC Motor Using Particle Swarm Algorithm
Subject Areas : electrical and computer engineering
Ahmad
Shirzadi
1
(Malek Ashtar University of Technology)
Arash
Dehestani Kolagar
2
(Malek Ashtar University of Technology)
Mohammad Reza
Alizadeh Pahlavani
3
(malek ashtar)
Keywords: Particle swarm optimization algorithm, brushless DC motor, transfer function, parameter estimation,
Abstract :
So far, comprehensive and extensive studies have been conducted on the brushless DC motor (BLDC), and a part of these studies focuses on the estimation of the parameters of the transfer function of this motor. Estimation of BLDC motor transfer function parameters is essential to study motor performance and predict its behavior. Therefore, an efficient, accurate and reliable parameter estimation method is needed. In this article, the problem of estimating the parameters of the transfer function of the inverter-fed BLDC motor set has been solved using particle swarm algorithms (PSO). The results of using this algorithm have been compared with the results of other optimization algorithms. The comparison of these results has shown that the PSO algorithm is an efficient, accurate and reliable method for solving the transfer function parameter estimation problem.
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