Research of Differential Evolution Algorithm for Motor Control

Article Preview

Abstract:

An improved differential evolution algorithm for solving nonlinear equations of electrical motor system is explored. The algorithm is to convert equations into an optimization problem and, by keeping consideration of the evolution process and adopting dynamic parameters adjusting mechanism, the algorithm can improve searching efficiency and implement real-time surveillance for population overlapping. The Chaos searching strategy is used for overlapping individual to further improve the ability of global optimization. Analysis results of induction motor motion parameters show that the improved differential evolution algorithm proposed in this paper has high efficiency and powerful global optimization searching ability.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

216-221

Citation:

Online since:

July 2014

Authors:

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] Y.X. Luo, W.G. Chen,Newton Chaotic Iterative Method and its Application in Induction Motor Motion, ,Journal of Chinese Power System and its Automation, 2006, 18(1): 24-28.

Google Scholar

[2] C. Chen, W. Cao,Application of Wu Method in Power System's Electromagnet Process in Sudden-short circuit Transient State, Journal of Chinese Motor Engneering, 2002, 22 (11): 16-19.

Google Scholar

[3] J. Xie, Y. Chen,A Chaos-based Approach to Obtain the Global Real Solutions of Burmester Points, China mechanical Engineering, 2002, 13(7): 608-710.

Google Scholar

[4] You-xin LUO, De-gang LIAO. Coupled chaotic maps Newton iteration method and Institutions l precision point kinematic synthesis. Mechanical transmission. 2007, 31(1): 28-30.

Google Scholar

[5] Luo Y.X., Li D.Z., Che X.Y., Hyper-chaotic Mapping Newton Iterative Method to Mechanism Synthesis. AMES, Journal of Mechanical Engineering, 2008, 54(9): 372-378.

Google Scholar

[6] XIE-Jin, CHEN-Yong. Burmester point finding method with rigid-body guidance based on chaos. China Mechanical Engineering, 2002, 13(7):608-710.

Google Scholar

[7] Riensche E, Meusinger J, Stimming et a1. Optimization of 200kW SOFC cogeneration power plant.Journal of Power Sources,1998,71(2):306-314.

DOI: 10.1016/s0378-7753(97)02726-2

Google Scholar

[8] OtaT,Koyama M,Wen C,eta1.Object-based modeling of SOFC system:dynamic behavior of micro-tube SOFC[J].Journal of Power Sources,2003,118(1—2): 430-439.

DOI: 10.1016/s0378-7753(03)00109-5

Google Scholar

[9] YU Tiemin, YAN Dongshu. Differential evolution algorithm for multi-objective optimization. Journal of Changchun University of Technology, 2006,16(4): 77-80.

Google Scholar

[10] X. L Zhao, X.M. Zhang, C. G. Duan. The performance research of high efficiency prime motor DIR-SOFC for decentralized energy system.Journal of Harbin Institute of Technology (New Series),2007,(14): 501-504.

Google Scholar

[11] LIU Zifa, YAN Jingxin, ZHANG Jianhua etc. Power system reactive power optimization based on animproved differential evolution algorithm. Power Grid Technology, 2007, 31 (18): 69-72.

DOI: 10.1049/cp.2009.1803

Google Scholar

[12] FAN Chunwei, JIANG Changsheng. Image encryption / decryption algorithm based on standard chaotic map. Journal of Harbin Institute of Technology, 2006, 38 (1) : 119-121.

Google Scholar