Comparison of Three Intelligence Algorithms on Parameter Identification of Jiles-Atherton Model

The Jiles-Atherton (J-A) theory is widely adopted in modeling electromagnetic transformers. Its performance is determined by five parameters, so parameter identification becomes a key issue. This paper quantitatively compares and analyzes the performance of three intelligence algorithms on identifying J-A model's parameters. Three intelligence algorithms are as follows: particle swarm optimization (PSO), artificial fish swarm algorithm (AFSA) and simulated annealing algorithm (SAA). The evaluation indexes are accuracy, speed and stability. The main conclusion is drawn that SAA performs better.