AIW-PSO 알고리즘을 이용한 매입형 동기전동기 최적화 설계에 관한 연구

In this paper, the novel particle swarm optimization (PSO), which adopt the strategy of adaptive distance-based inertia weight is proposed to get the decreasing analysis time and accurate performance of the algorithm. The basic searching strategy is that divide the inner search area and outer search area. When the particles are located in the inner or outer search area, the inertia weight is set as specified value, based on the position. In the inner search area, the inertia weight is changed on the distance equation which calculate the length between the position of particle and the global minimum point. To verify the effectiveness of the novel PSO algorithm, the conventional and proposed algorithm are compared with the Branin, Goldstein and Restrigin test functions. Moreover, the proposed novel PSO algorithm is applied to design the interior permanent magnet synchronous motor(IPMSM).