Continuous quantum ant colony optimization and its application to optimization and analysis of induction motor structure

Author

Li, Weili ; Yin, Qiaoyu ; Zhang, Xiaochen

Author_Institution

Coll. of Electr. & Electron. Eng., Harbin Univ. of Sci. & Technol., Harbin, China

fYear

2010

fDate

23-26 Sept. 2010

Firstpage

313

Lastpage

317

Abstract

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 its current position. And quantum bits are updated by quantum rotation gate to make ant´s position changed. Some quantum bits are mutated by quantum non-gate to increase the population diversity. Numerical simulation results show that new algorithm has better global search capability and faster convergence rate than classical ant colony optimization. Furthermore, the new algorithm is applied to optimization for motor structure parameters successfully, and satisfactory optimization results are obtained. A new effective method for motor structure optimization has been suggested based on continuous quantum ant colony optimization.

Keywords

induction motors; optimisation; power engineering computing; quantum computing; continuous quantum ant colony optimization; continuous space optimization; induction motor structure; motor structure optimization; motor structure parameters; population diversity; quantum bits; quantum computation; Air gaps; Computational modeling; Logic gates; Optimization; ant colony optimization; continuous quantum ant colony optimization; induction motor; optimal design; structure optimization;

fLanguage

English

Publisher

ieee

Conference_Titel

Bio-Inspired Computing: Theories and Applications (BIC-TA), 2010 IEEE Fifth International Conference on

Conference_Location

Changsha

Print_ISBN

978-1-4244-6437-1

Type

conf

DOI

10.1109/BICTA.2010.5645311

Filename

5645311