Parameter Identification of Jiles-Atherton Model Based on Levy Whale Optimization Algorithm

The Jiles-Atherton model is key to researching the hysteresis loop. focus of scholars across various countries has always been parameter identification model. This paper on Levy whale optimization algorithm (LWOA), based (WOA), proposes overcome disadvantage that WOA tends involve local optimum. recommended uses flight strategy instead encircling prey policy since former improves global search. Therefore, new better at stability and calculation accuracy. To substantiate efficacy proposed algorithm, it tested against six benchmark functions compared with WOA, particle swarm (PSO), grey wolf (GWO), shuffled frog leaping (SFLA). In addition, applied realize two classical engineering problems, such as tension/compression spring welded beam design issues. experimental findings reveal highly competitive metaheuristic optimizers algorithm’s performance. address poor J-A identification, an improved method for k reduced ranges parameters a α were combined LWOA. called C-LWOA, which LWOA, PSO, GWO, SFLA, cuckoo search (CS) data reported in literature. Moreover, simulation results demonstrate accuracy by C-LWOA was significantly strengthened. Equally important, error within 0.2%. Finally, subsequently used fit actual measurements loop permalloy.