Enhancing Improved Sparrow Algorithm for Multi-Parameter Identification of Permanent Magnet Synchronous Motor
In response to the issues of insufficient convergence speed,poor global searching ability and insuf-ficient accuracy in multi parameter identification of permanent magnet synchronous motor,a multi parameter identification method of permanent magnet synchronous motor based on enhancing improved sparrow search algorithm is proposed. Firstly,initialize the population using chaotic mapping to improve the search space;U-sing adaptive t-distribution to update the position of enrollees and avoid getting stuck in local search space;A-dopting a reverse learning strategy to improve the convergence speed of all individuals in the population;Se-lect the global optimal through greedy rules. This algorithm enhances the ability of the algorithm to jump out of local optima,improve convergence speed and accuracy by enhancing processes such as population initial-ization,search space,search algorithm,and optimal selection. Selecting typical standard testing functions for performance evaluation of the algorithm,the results reveal better convergence speed,accuracy,and global op-timization ability. Through verification of simulation and experiment,compared with the general sparrow search algorithm,the improved sparrow search algorithm,the genetic algorithm and the particle swarm optimi-zation,the proposed enhancing improved sparrow search algorithm has faster identification speed and higher convergence accuracy in multi parameter identification of permanent magnet synchronous motor.
万方数据
维普
