Journal of the Korean Institute of Illuminating and Electrical Installation Engineers (조명전기설비학회논문지)

The Korean Institute of IIIuminating and Electrical Installation Engineers (한국조명전기설비학회)
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Optimum Design of a linear Induction Motor using Genetic Algorithm and Neural Network

유전알고리즘과 신경회로망을 이용한 선형유도전동기의 최적설계

  • 김창업 (호서대학교 전기정보통신공학부)
  • Published : 2003.09.01
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Abstract

In this paper, a new optimum design method is proposed for the linear induction motor(LIM). The Genetic Neural Network(GNN) is introduced in the optimum design of LIM and the simulation result is compared with the Genetic Algorithm(GA) and Neural Network(NN). The maximum thrust and trust/weight are selected as the object functions. The comparison showed that the proposed method is better than GA and NN.

본 논문에서는 유전 알고리즘과 신경 회로망을 이용하여 선형유도전동기의 최적화 설계 방법에 대하여 연구하였다. 최대 추력 및 추력/중량을 목적함수로 하여 유전알고리즘, 신경회로망, 유전알고리즘과 신경회로망의 합성에 의한 방법으로 선형유도전동기의 최적설계를 한 결과 제안한 방법이 가장 우수함을 확인하였다.

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References

  1. Ki-Hwa Kim, Multicriteria Structural Optimization by Genetic Algorithm, Seoul National University, 1994.
  2. Sung-Ok Hong, Optimum Design of a Linear Induction Motor using Genetic Algorithm, Hoseo University, 2000.
  3. David E. Goldberg, Genetic Algorithm in Search, Optimizati on, and Machine Learning, Addison-wesley, pp. 1-57, 1989.
  4. Dong-Jin Bae, Analysis and Design of the Induction Motor using Neural Network, Seoul National University, 1996.
  5. Seung-Beum Chung, A New Algorithm for Structural Optimization of Neural Networks, KAIST, 1997.
  6. Dal-Ho Im, Cheol-Jick lee, Seung-Chan Park, "Optimization of Design Variables of SLIM using the Equivalent Circuit Analysis and SUMT," KIEE Trans., vol. 42, no. 5, pp.340-343, 1993.