Abstract
The paper deals with application of a genetic algorithm for setting parameters of the speed controller in the control structure of the A.C. drive with the vector controlled induction motor. In the first part of the paper, the design of the genetic algorithm for the PI controller is presented. The second part shows possibilities of the modern simulation method using hardware in the loop simulation method in the software environment Matlab-Simulink and its implementation using modern digital signal controller. In the last part, simulation results for different speed and torque changes of the induction motor are shown. Rightness of the designed genetic algorithm has been verified by simulations then the method has been implemented into DSP control system.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Finch, J.W., Giaouris, D.: Controlled AC Electrical Drives. IEEE Transactions on Industrial Electronics 55(2), 481–491 (2008)
Vas, P.: Artificial-Intelligence-Based Electrical Machines and Drives. Oxford science publication (1999)
Holtz, J.: Sensorless Control of Induction Motor Drives. Proceedings of the IEEE 90(8), 1359–1394 (2002)
Abachizadeh, M., Yazdi, M.R.H., Yousefi-Koma, A.: Optimal Tuning of PID Controllers Using Artificial Bee Colony Algorithm. In: Conference Proceedings of the International Conference on Advanced Intelligent Mechatronics, Montreal, Canada, pp. 379–384 (2010)
Amamra, S.A., Barazane, L., Boucherit, M.S.: A New Approach of the Vector Control of the Induction Motor Using an Inverse Fuzzy Model. International Review of Electrical Engineering - IREE 3(2), 361–370 (2008)
Perdukova, D., Fedor, P.: Fuzzy Model Based Control of dynamic System. JEE-Journal of Electrical Engineering 7(3) (2007)
Rajasekhar, A., Abraham, A., Jatoth, R.K.: Controller Tuning Using a Cauchy Mutated Artificial Bee Colony Algorithm. In: Corchado, E., Snášel, V., Sedano, J., Hassanien, A.E., Calvo, J.L., Ślęzak, D. (eds.) SOCO 2011. AISC, vol. 87, pp. 11–18. Springer, Heidelberg (2011)
Viteckova, M., Vitecek, A.: Selected Methods of Adjusting Controllers. VSB-Technical University of Ostrava (2011)
Goldberg, D.E.: Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley Publishing Company, Boston (1989)
Brandstetter, P.: A.C. Controlled Drives - Modern Control Methods. VSB-Technical University of Ostrava (1999)
Elmas, C., Yigit, T.: Genetic Algorithm Based On-line Tuning of a PI Controller for a Switched Reluctance Motor Drive. Electric Power Comp. and Syst. 35(6), 675–691 (2007)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Brandstetter, P., Dobrovsky, M. (2013). Speed Control of A.C. Drive with Induction Motor Using Genetic Algorithm. In: Herrero, Á., et al. International Joint Conference CISIS’12-ICEUTE´12-SOCO´12 Special Sessions. Advances in Intelligent Systems and Computing, vol 189. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33018-6_35
Download citation
DOI: https://doi.org/10.1007/978-3-642-33018-6_35
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33017-9
Online ISBN: 978-3-642-33018-6
eBook Packages: EngineeringEngineering (R0)