지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2011.11
- 수록면
- 856 - 863 (8page)
이용수
초록· 키워드
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In this paper a novel method of the Ant Colony Optimization algorithm for rotor position estimation in Switched Reluctance Motors is presented. The data provided by the initial assumptions is one of the important aspects used to solve the problems relative to an Ant Colony algorithm. Considering the nature of a real ant colony, it was found that the ants have no primary data for deducing which is the shortest path in their initial iteration. They also do not have the ability to see the food sources at a distance. According to this point of view, a novel method is presented in which the rotor pole position relative to the corresponding stator pole in a switched reluctance motor is estimated with high accuracy using the active and inactive phase parameters. This new method gives acceptable results such as a desirable convergence together with an optimized and stable response. To the best knowledge of the authors, such an analysis has not been carried out previously.
목차
Abstract
Ⅰ. INTRODUCTION
Ⅱ. ACO ALGORITHM EVALUATION
Ⅲ. PROBLEM STATEMENT
Ⅳ. ENHANCED METHOD
Ⅴ. IMPLEMENTATION OF THE NEW METHOD IN ROTORPOSITION ESTIMATION
Ⅵ. CONCLUSION
REFERENCES
참고문헌 (31)
참고문헌 신청
J. Kennedy / 2006 / Handbook of Nature-Inspired and Innovative Computing / Swarm intelligence :187~219
M. Dorigo / 2004 / Ant colony optimization / MIT Press
H. Bai / 2006 / A survey on application of swarm intelligence computation to electric power system / The Sixth World Congress on Intelligent Control and Automation :7587~7591
S. Rahmatizadeh / 2009 / The ant-bee routing algorithm: a new agent based nature-inspired routing algorithm / Journal of Applied Sciences 9(5):983~987
H. M. Emara / 2008 / Parameter identification of induction motor using modified particle swarm optimization algorithm / IEEE International Symposium on Industrial Electronics :841~847
M. Dorigo / 2004 / Ant colony optimization / MIT Press
H. Bai / 2006 / A survey on application of swarm intelligence computation to electric power system / The Sixth World Congress on Intelligent Control and Automation :7587~7591
S. Rahmatizadeh / 2009 / The ant-bee routing algorithm: a new agent based nature-inspired routing algorithm / Journal of Applied Sciences 9(5):983~987
H. M. Emara / 2008 / Parameter identification of induction motor using modified particle swarm optimization algorithm / IEEE International Symposium on Industrial Electronics :841~847
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UCI(KEPA) : I410-ECN-0101-2013-560-001034219