Parameter identification of Jiles–Atherton model using the chaotic optimization method
| Autor: | Ana Jovanovic, Luka Lazovic, Vesna Rubežić |
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| Rok vydání: | 2018 |
| Předmět: |
010302 applied physics
Fitness function Computer science Applied Mathematics 020208 electrical & electronic engineering Chaotic Particle swarm optimization 02 engineering and technology 01 natural sciences Pattern search Computer Science Applications Hysteresis Computational Theory and Mathematics 0103 physical sciences Genetic algorithm Simulated annealing 0202 electrical engineering electronic engineering information engineering Jiles-Atherton model Electrical and Electronic Engineering Algorithm |
| Zdroj: | COMPEL - The international journal for computation and mathematics in electrical and electronic engineering. 37:2067-2080 |
| ISSN: | 0332-1649 |
| DOI: | 10.1108/compel-11-2017-0496 |
| Popis: | Purpose The purpose of this paper is to propose a chaotic optimization method for identifying the parameters of the Jiles–Atherton (J-A) hysteresis model. Design/methodology/approach The J-A model has five parameters which are assigned with physical meaning and whose determination is demanding. To determine these parameters, the fitness function, which represents the difference between the measured and the modeled hysteresis loop, is formed. Optimal parameter values are the values that minimize the fitness function. Findings The parameters of J-A model for three magnetic materials are determined. The model with the optimal parameters is validated using measured data and comparison with particle swarm optimization algorithm, genetic algorithm, pattern search and simulated annealing algorithm. The results show that the proposed method provides better agreement between measured and modeled hysteresis loop than other methods used for comparison. The proposed method is also suitable for simultaneous optimization of multiple hysteresis loops. Originality/value Chaotic optimization method is implemented for the first time for J-A model parameter identification. Numerical comparisons with results obtained with other optimization algorithms demonstrate that this method is a suitable alternative in parameters identification of J-A hysteresis model. Furthermore, this method is easy to implement and set up. |
| Databáze: | OpenAIRE |
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