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[1] Zhuang Yingchao, Yu Haitao, Xia Jun, Hu Minqiang, et al. Optimization of linear induction machinesbased on a novel adaptive genetic algorithm [J]. Journal of Southeast University (English Edition), 2009, 25 (2): 203-207. [doi:10.3969/j.issn.1003-7985.2009.02.013]
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Optimization of linear induction machinesbased on a novel adaptive genetic algorithm()
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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:
25
Issue:
2009 2
Page:
203-207
Research Field:
Electrical Engineering
Publishing date:
2009-06-30

Info

Title:
Optimization of linear induction machinesbased on a novel adaptive genetic algorithm
Author(s):
Zhuang Yingchao1 Yu Haitao1 Xia Jun2 Hu Minqiang1
1School of Electrical Engineering, Southeast University, Nanjing 210096, China
2 Jiangsu Science and Technology Museum, Nanjing 210013, China
Keywords:
adaptive genetic algorithm linear induction machine uniform design
PACS:
TM359.4
DOI:
10.3969/j.issn.1003-7985.2009.02.013
Abstract:
In order to improve the thrust-power ratio index of the linear induction motor(LIM), a novel adaptive genetic algorithm(NAGA)is proposed for the design optimization of the LIM.A good-point set theory that helps to produce a uniform initial population is used to enhance the optimization efficiency of the genetic algorithm.The crossover and mutation probabilities are improved by using the function of sigmoid and they can be adjusted nonlinearly between average fitness and maximal fitness with individual fitness.Based on the analyses of different structures between the LIM and the rotary induction motor(RIM)and referring to the analysis method of the RIM, the steady-state characteristics of the LIM that considers the end effects of the LIM is calculated and the optimal design model of the thrust-power ratio index is also presented.Through the comparison between the optimal scheme and the old scheme, the thrust-power ratio index of the LIM is obviously increased and the validity of the NAGA is proved.

References:

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Memo

Memo:
Biographies: Zhuang Yingchao(1983—), male, gradate;Yu Haitao(corresponding author), male, doctor, professor, htyu@seu.edu.cn.
Citation: Zhuang Yingchao, Yu Haitao, Xia Jun, et al.Optimization of linear induction machines based on a novel adaptive genetic algorithm[J].Journal of Southeast University(English Edition), 2009, 25(2):203-207.
Last Update: 2009-06-20