Artificial immune system for parameter estimation of induction motor

Expert Systems with Applications

Volumn 37, Issue 8, 2010, Pages 6109-6115

  Sakthivel, V P ^a   Bhuvaneswari, R ^a   Subramanian, S ^a  

^a ANNAMALAI UNIVERSITY   (India)

Author keywords

Genetic algorithm; Immune algorithm; Induction motor; Parameter estimation

Indexed keywords

ARTIFICIAL IMMUNE SYSTEM; CONVENTIONAL METHODS; EQUIVALENT CIRCUIT PARAMETER; IMMUNE ALGORITHM; IMMUNE ALGORITHMS; INDUCTION MOTOR MODEL; INDUCTION MOTOR PARAMETERS; LOCKED ROTOR; MINIMIZATION PROBLEMS; OPERATING CONDITION; SQUARE ERRORS; STEADY STATE;

ELECTRIC NETWORK PARAMETERS; GENETIC ALGORITHMS; INDUCTION MOTORS; METAL ANALYSIS; OPTIMIZATION;

PARAMETER ESTIMATION;

EID: 77951206331     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2010.02.034     Document Type: Review

References (29)

1. Abdelhadi B., Benoudjit A., and Nait Said N. Identification of induction machine parameters using a adaptive genetic algorithm. Electric Power Components and Systems 32 (2004) 767-784
2. Alonge F., Dippolito F., Ferrante G., and Raimondi F.M. Parameter identification of induction motor model using genetic algorithms. IEE Proceedings on Control Theory Applications 145 6 (1998)
3. Ansuj S., Shokooh F., and Schinzinger R. Parameter estimation for induction machines based on sensitivity analysis. IEEE Transactions on Industry Applications 25 6 (1989) 1035-1040
4. Bae D. Determination of induction motor parameters by using neural network based on FEM results. IEEE Transactions on Magnetics 33 (1997) 1924-1927
5. Bishop, R. R., & Richards, G. G. (1990). Identifying induction machine parameters using a genetic optimization algorithm. Proceedings on IEEE South East Conference, 2, 476-479.
6. Chun J.S., Kim M.K., and Jung H.K. Shape optimization of electromagnetic using immune algorithm. IEEE Transactions on Magnetics 33 2 (1997) 1867-1879
7. Chun J.S., Lim J.P., and Yoon J.S. Optimal design of synchronous motor with parameter correction using immune algorithm. IEEE Transactions on Energy Conversion 14 3 (1999) 610-615
8. Farmer J.D., Packard N.H., and Perelson A.A. The immune system adaption and machine learning. Physica D 22 (1986) 187-204
9. Filho E.B.S., Lima A.M.N., and Jacobina C.B. Parameter estimation for induction machines via non-linear least squares method. IECON (1991) 639-643
10. Fogel D.B. Evolutionary computation: Toward a new philosophy of machine intelligence. 2nd ed. (2000), IEEE Press, Piscataway, NJ
11. Huang K.S., Kent W., Wu Q.H., and Turner D.R. Parameter identification for FOC induction motors using genetic algorithm with improved mathematical model. Electric Power Components and Systems 29 3 (2001) 247-258
12. Koubaa Y. Recursive identification of induction motor parameters. Journal of Simulation Modeling Practice and Theory 12 5 (2004) 363-381
13. Lin C.H., Chen C.S., Wu C.J., and Kang M.S. Application of immune algorithm to optimal switching operation for distribution loss minimization and loading balance. IEE Proceedings on Generation Transmission and Distribution 150 2 (2003) 183-189
14. Lindenmeyer D., Dommel H.W., Moshref A., and Kundur P. An induction motor parameter estimation method. Electrical Power and Energy Systems 23 (2001) 251-262
15. Michael, T. W., & Ronald, G. H. (1995). Identification and control of induction machines using artificial neural networks. IEEE Transactions on Industry Applications Proc.
16. Mitsumoto, N., Fukuda, T., & Arai, F. (1994). The immune mechanism, adaption, learning for the multi agent system. In IEEE symposium on emerging technologies and factory automation, Tokyo, Japan.
17. Mori K., Tsukiyama M., and Fukuda T. Immune algorithm with searching diversity and its application to resource allocation problem. Trans. Inst. Electrical Engineering Japan 10 (1993) 872-878
18. Nangsue P., Pillay P., and Conry S. Evolutionary algorithms for induction motor parameter determination. IEEE Transactions on Energy Conversion 14 3 (1994) 447-453
19. Nollan, R., Pillay, P., & Haque, T. (1994). Application of genetic algorithms to motor parameter determination. In Proceedings of 1994 IEEE-IAS conference Denvar (pp. 47-54).
20. Orlowska Kowalska T., Lis J., and Szabat K. Identification of the induction motor parameters using soft computing methods. Computation and Mathematics in Electrical and Electronics Engineering 25 1 (2006) 181-192
21. Pedra J., and Corcoles F. Estimation of induction motor double-cage model parameters from manufacturer data. IEEE Transactions on Energy Conversion 19 2 (2004)
22. Pedra J., and Sainz L. Parameter estimation of squirrel-cage induction motors without torque measurements. IEE Proceedings on Electric Power Application 153 2 (2006) 263-269
23. Pillay P., Nollan R., and Haque T. Application of genetic algorithms to motor parameter determination for transient torque calculations. IEEE Transactions on Industry Applications 33 5 (1997)
24. Rahimpour E., Rashtchi V., and Pesaran M. Parameter identification of deep-bar induction motors using genetic algorithm. Electrical Engineering 89 (2007) 547-552
25. Say, M. G. (1983). Alternating current machines. Pitman.
26. Stephan J., Bodson M., and Chiasson J. Real time estimation of induction motor parameters. IEEE Transactions on Industry Applications 30 3 (1994) 746-759
27. Toliyat H.A., Levi E., and Raina M. A review of RFO induction motor parameter estimation techniques. IEEE Transactions on Energy Conversion 18 3 (2003) 271-283
28. Ursem, R. K., & Vadstrup, P. (2003). Parameter identification of induction motors using differential evolution. In The 2993 congress on evolutionary computation CEC'03 (Vol. 2, pp. 790-796).
29. Wang K., Chiasson J., Bodson M., and Tolbert L.M. A nonlinear least squares approach for identification of the induction motor parameters. IEEE Transactions on Automatic Control 50 10 (2005) 1622-1628