An improved adaptive firefly algorithm for PI parameter optimization of permanent magnet synchronous motor

A parameter optimization algorithm for the PI controller of permanent magnet synchronous motor (PMSM) based on improved adaptive firefly algorithm (IAFA) is proposed. The PI parameters of current and speed are set by improved adaptive firefly algorithm. This paper introduces 7 dimensions firefly population and adaptive step adjustment mechanism in the algorithm, which is fast and convenient to obtain the optimal solution accurately. The traditional parameter optimization method usually uses an operator to get the target parameter after repeated debugging in the actual system, which is inefficient and relies heavily on production experience. In order to optimize this problem, multidimensional population and adaptive step adjustment strategy are proposed to speed up the iteration and get the global optimal. The results demonstrate that PMSM-IAFA has fast convergence rate and high computational accuracy. It significantly outperforms the other state-of-the-art FA variants in majority of the tested instances.