基于连续量子蚁群优化的感应电机电磁特性计算与分析

Digests of the 2010 14th Biennial IEEE Conference on Electromagnetic Field Computation Pub Date : 2010-05-09 DOI:10.1109/CEFC.2010.5481292

Li Weili, Yin Qiaoyu, Zhang Xiaochen

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引用次数: 3

摘要

将量子计算引入到蚁群优化中，提出了一种新的用于连续空间优化的量子蚁群算法。每只蚂蚁携带一组代表蚂蚁当前位置的量子比特，通过量子旋转门对量子比特进行更新，使蚂蚁的位置发生变化，通过量子非门对部分量子比特进行突变，增加蚁群的多样性。从理论上证明了算法的收敛性。数值仿真结果表明，该算法比经典蚁群算法具有更好的全局搜索能力和更快的收敛速度。最后，将该算法成功地应用于异步电动机的优化设计中，得到了优化结果。提出了一种有效的基于连续量子蚁群优化的异步电机设计方法。

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Calculation and analysis of electromagnetic in an induction motor based on continuous quantum ant colony optimization

A new kind of quantum ant colony algorithm for continuous space optimization is proposed in this paper, by the introduction of quantum computation into ant colony optimization. Each ant carries a group of quantum bits representing the current location of ant, and quantum bits are updated by quantum rotation gates to make the location of ants changed, some quantum bits are mutated by quantum non-gates to increase the population diversity in this algorithm. The convergence of proposed algorithm is proved theoretically. The numerical simulation results show that the new algorithm has better global search capability and faster convergence rate than classical ant colony optimization. Furthermore, the new algorithm is applied to the optimal design of an induction motor successfully, and optimization results are obtained. An effective design method for induction motor has been suggested based on continuous quantum ant colony optimization.

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Digests of the 2010 14th Biennial IEEE Conference on Electromagnetic Field Computation

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