원문정보
A Study on Design of Interior Permanent Magnet Synchronous Motor using Adaptive Inertia Weight Particles Swarm Optimization Algorithm
초록
영어
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).
목차
I. 서론
II. PSO 알고리즘
1. 기존 AIW-PSO 알고리즘
2. 개선된 AIW-PSO 알고리즘
3. AIW-PSO 알고리즘의 비교
III. 제안된 알고리즘의 적용을 통한 IPMSM 설계
IV. 결론
감사의 글
[참고문헌]