Improved Artificial Fish Swarm Algorithm Applied on the Static Model of the Induction Motor Parameter Identification

Jing Yong Lv

doi:10.4028/www.scientific.net/AMM.220-223.753

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 220-223Improved Artificial Fish Swarm Algorithm Applied...

Improved Artificial Fish Swarm Algorithm Applied on the Static Model of the Induction Motor Parameter Identification

Abstract:

According to the induction motor operating characteristics, application of improved artificial fish swarm algorithm based on the simplex method to solve the equivalent circuit model parameters identification problem. Gives a detailed calculation steps and the curve of function expressions. Finally, the identification results and identification using genetic algorithm result is compared to prove that the accuracy of the identification results of the improved artificial fish swarm algorithm having higher precision.

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Periodical:

Applied Mechanics and Materials (Volumes 220-223)

Pages:

753-761

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.220-223.753

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Cite this paper

Online since:

November 2012

Authors:

Jing Yong Lv

Keywords:

Artificial Fish-Swarm Algorithm (AFSA), Induction Motor (IM), Parameter Identification, Simplex Method

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References

[1] D. Lindenmeye, H.W. Dommel, A.Moshref, An Induction Motor Parameter Identification Method , J. JElectrical Power and Energy Systems, 23(2011)251-262.

DOI: 10.1016/s0142-0615(00)00060-0

Google Scholar

[2] Paolo Castaldi, Andrea Tilli, Parameter Identification of Induction Motor at Standstill With Magnetic Flux Monitoring, J. IEEE Transactions on Control Systems Technology, Vol.13, No.3, May, 2005, pp.386-400.

DOI: 10.1109/tcst.2004.841643

Google Scholar

[3] Paolo Castaldi, Walter Geri, Marcello Montanari , Andrea Tilli, A New Adaptive Approach for On-Line Parameter and State Identification of Induction Motors, J. Control Engineering Practice, Vol.13, January, 2005, pp.81-94.

DOI: 10.1016/j.conengprac.2004.02.008

Google Scholar

[4] C. Belloc, H. Zhang, Y. Vagapov, P. Monero, A Step Voltage Response Method for Identification of Induction Motor Parameters at Standstill, J. IEEE International Conference on Electro Information Technology, May, 2006, pp.109-112.

DOI: 10.1109/eit.2006.252171

Google Scholar

[5] Rajib Mikail, Kazi Mujibur Rahman, A Sensor-less Adaptive Rotor Parameter Identification Method for Three Phase Induction Motor, 5th International Conference on Electrical and Computer Engineering ICECE 2008, December, 2008, pp.20-22.

DOI: 10.1109/icece.2008.4769295

Google Scholar

[6] R. Mujal, O. Boix, P.J. Gamez, R. Castilla, J. lloveas, Experimental Analysis of the Three-Phase Induction Motor with Spiral Sheet Rotor, J. Journal Electrical Engineering, No.9, December, 2009, pp.251-261.

DOI: 10.1007/s00202-009-0141-y

Google Scholar

[7] V.P. Sakthivel, R. Bhuvaneswari, S, Subramanian, Multi-objective Parameter Identification of Induction Motor Using Particle Swarm Optimization, J. Engineering Applications of Artificial Intelligence, Vol.23, 2010, pp.302-311.

DOI: 10.1016/j.engappai.2009.06.004

Google Scholar

[8] Li Xiaolei, Shao Zhijiang, Qian Jixin, An optimizing method based on autonomous animal:fish swarm algorithm, J. Systems Engineering-theory & practice, 2002, 22(11), pp.32-38.(in Chinese)

Google Scholar

[9] Guo Ke, Chen Ling, Wei Youhua, Optimization method and its application, M. China high education press, 2007, pp.115-119.

Google Scholar

[10] Wang Guolian, Hong Yi, Zhao Fuqing etc, An improved algorithm of artificial fish swarm, J. Computer engineering, 2008(19), pp.192-194.(in Chinese)

Google Scholar

[11] Wang Guolian, Hong Yi, Zhao Fuqing etc, A simplified artificial fish swarm algorithm, J. Small miniature computer systems, 2009, 30 (8), pp.1663-1667.(in Chinese)

Google Scholar

[12] Akbaba M, Taleb M & Rumeli A, Improved identification of induction machine parameters, J. Electric Power System Research, 1995,(34), pp.65-73.

DOI: 10.1016/0378-7796(95)00958-k

Google Scholar

[13] Huang Kaisheng, Wu Q h, Genetic algorithm in dynamic model of induction motor parameter identification of use , J. Journal of Chinese electrical engineering, 2000,(8), pp.37-41.(in Chinese)

Google Scholar

[14] Liu Wenfeng, Huang Kaisheng, The genetic algorithm in induction motor static model parameters identification of use, J. Journal of Guangdong university, 2002,(4), pp.4-8.(in Chinese)

Google Scholar