Adaptive Cuckoo Search Algorithm for the Speed Control System of Induction Motor

Volume 2, Issue 1, February 2017     |     PP. 1-13      |     PDF (444 K)    |     Pub. Date: February 21, 2017
DOI:    314 Downloads     5741 Views  

Author(s)

Lingzhi Yi, College of Information Engineering, Xiangtan University, Hunan Pro., ,Xiangtan, 411105, P.R. China; Hunan Province Cooperative Innovation Center for Wind Power Equipment and Energy Conversion.
Yue Liu, College of Information Engineering, Xiangtan University, Hunan Pro., ,Xiangtan, 411105, P.R. China.
wenxin Yu, School of Information and Electrical Engineering, Hunan University of Science and Technology, Hunan Pro., , Xiangtan 411201, P.R. China.
Genping Wang, Shenzhen polytechnic, Guangdong Pro., Shenzhen, 51800, P.R. China.
Yongbo Sui, College of Information Engineering, Xiangtan University, Hunan Pro., ,Xiangtan, 411105, P.R. China.

Abstract
Optimization techniques are becoming more popular for the improvement in control of induction motor. Many intelligent algorithms have been used to improve performance of induction motor, Cuckoo search algorithm as an optimization algorithm can be used to find the optimal parameters of PID controller for induction motor. In this paper, cuckoo search algorithm is proposed to obtain optimized parameters of PID for indirect vector control in induction motor drive system. Normally, the parameters of the CS are fixed constants which may result in affecting the algorithm efficiency. To cope with this issue, we properly tune the parameters of the CS and propose an adaptive cuckoo search algorithm to enhance the convergence rate and accuracy of the CS. Compared with cuckoo search algorithm,genetic algorithm, and particle swarm optimization,the simulation results show that the proposed method has excellent dynamic and static performance.

Keywords
Induction motor; PID controller; Cuckoo Search algorithm (CS); Adaptive cuckoo search algorithm (ACS)

Cite this paper
Lingzhi Yi, Yue Liu, wenxin Yu, Genping Wang, Yongbo Sui, Adaptive Cuckoo Search Algorithm for the Speed Control System of Induction Motor , SCIREA Journal of Electrical Engineering. Volume 2, Issue 1, February 2017 | PP. 1-13.

References

[ 1 ] B.K Bose “modern power electronics and ac drives “Prentice-Hall Publication, Englewood Cliffs, New Jersey,1986
[ 2 ] Kim D K, Kwon B I. A Novel Equivalent Circuit Model of Linear Induction Motor Based on Finite Element Analysis and its Coupling With External Circuits[J]. IEEE Transactions on Magnetics, 2006, 42(10):3407-3409.
[ 3 ] Shepard F H. Apparatus for variable speed drive of an induction motor from a fixed frequency AC source: US, US 4600872 A[P]. 1986.
[ 4 ] Qi X, Zhang J. Study on Adaptive PID Control Algorithm Based on RBF Neural Network[J]. Telkomnika Indonesian Journal of Electrical Engineering, 2015, 13(2).
[ 5 ] Goldberg, D.E., “Genetic Algorithms in Search,” Optimization and Machine Learning, Reading, Mass., Addison Wesley, 1989.
[ 6 ] Kennedy, J. and Eberhart, R.C., “Particle swarm optimization,” Proc. Of IEEE International Conference on Neural Networks, Piscataway, NJ., 1995, pp. 1942-1948.
[ 7 ] Yang X, Deb S, “Cuckoo search via levey flights,” Word congress on nature and biologically inspried computing’ NABIC-2009, vol 4. Coimbatore, pp. 210-214.
[ 8 ] Rui-minJia; Deng-xu.Complexvalued cuckoo search with local search 2013 Ninth International Conference on Natural Computation (ICNC),Shenyang, China ,2013, pp 1804-1808.
[ 9 ] Shaija P J, Daniel A E. An Intelligent Speed Controller Design for Indirect Vector Controlled Induction Motor Drive System[J]. Procedia Technology, 2016, 25:801-807.
[ 10 ] Payne, R.B., Sorenson, M.D., Klitz, K., “The cuckoos,” Oxford University Press, 2005.
[ 11 ] Brown, C., Liebovttch, L.S., Glendon, R., “Lévy flights in Dobe Ju/hoansi foraging patterns,” Human Ecology, 2007, 35, pp. 129-138.
[ 12 ] Yang, X.S., Deb, S., “Engineering optimization by cuckoo search,” International Journal of Mathematical Modelling and Numerical Optimization, 2010, 1(4), pp. 330-343.