Comparison of Several Improved Versions of Particle Swarm Optimizer Algorithm for Parameter Estimation of Squirrel-Cage Induction Motors

Mohammad Yazdani-Asrami, Mehran Taghipour Gorjikolaie, S. Asghar Gholamian

Abstract


In this paper, three versions of Particle Swarm Optimization (PSO) are proposed to estimate the equivalent
circuit parameters of squirrel cage induction motor. It is believed that how inertia weight changes during
iterations can impact on final results. Constricted coefficients, linear model and exponential version are
used as inertia weight, each of them presents different variations for inertia weight and consequently for
particle movements and speed of such movements. In the linear version, particles start searching process
with high speed and their speed will decrease by constant ramp, this kind of variation let to search all
solution space in a short time and local search at the final iterations with low speed, also exponential
version presents same treatment as linear version with non-linear variations in inertia weight and speed of
movement. But, mathematical analysis shows that they trap into local minima and scientists presents
constricted version to solve this problem. In order to evaluate proposed versions additional to make
changing in PSO’s version, sensitivity of proposed methods is analyzed using three sets of data. Results
confirm the ability of proposed method which can estimate parameters with a possible least error


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Copyright (c) 2015 Mohammad Yazdani-Asrami, Mehran Taghipour Gorjikolaie, S. Asghar Gholamian

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Universiti Teknologi MARA Cawangan Perlis