Distance based Intelligent Particle Swarm Optimization for Optimal Design of Permanent Magnet Synchronous Machine

In this study, we propose a novel intelligent particle swarm optimization(PSO). In case of PSO, when particles approach to optimum point, particles roam near global optimum. Therefore, PSO takes unnecessary function call and long convergence time. In order to solve these problems, we propose distance based intelligent particle swarm optimization(DbIPSO). DbIPSO calculate distance of every particle and when distance is lower than assigned value, best particle absorbs near particles to reduce function call and convergence time. By applying proposed algorithm to optimal design of permanent magnet synchronous machine, we validate its effectiveness and performance.