Tuning Of PID Speed Controller in FOC of Induction Motor Based On Particle Swarm Optimization, Genetic Algorithm and Fuzzy Logic

P. Lakshmana Kumar*, P. Dhana Selvi **
*,** Assistant Professor,Department of Electrical and Electronics Engineering N.B.K.R. Institute of Science and Technology ,Vidhyanagar,A.P.,India.
***Associate Professor,Department of Electrical and Electronics Engineering N.B.K.R. Institute of Science and Technology ,Vidhyanagar,A.P.,India.
Periodicity:October - December'2008
DOI : https://doi.org/10.26634/jee.2.2.307

Abstract

Because of the low maintenance and robustness, induction motors have many applications in the industries. However, many applications need variable speed operations. The required speed can be controlled by conventional controllers like P, PI and PID. PID controllers are very common in industrial systems applications. The tuning of these controllers is governed by system nonlinearities and continuous parameter variations. In this paper, a complete and rigorous comparison is made between three tuning algorithms. The PID controller was used in a speed control loop in a Field Oriented Control (FOC) scheme applied on an induction motor. The first method applies Particle Swarm Optimization (PSO) strategy, second method applies Genetic Algorithm (GA) and the other one makes use of Fuzzy Logic (FL) tuning scheme. FOC is then tested with the three schemes for three cases, with normal operating conditions, with a sudden change in load torque applied to the motor and with increased rotor resistance. The simulated design is tested using various tool boxes in MATLAB. The results obtained show that the PSO tuning technique provides better speed control performance under normal operating conditions as well as under the conditions where system parameter variations occur.

Keywords

Induction motor, speed control, field oriented control, fuzzy logic, Genetic Algorithm and Particle Swarm Optimization.

How to Cite this Article?

P. Lakshmana Kumar and P. Dhana Selvi (2008). Tuning Of PID Speed Controller in FOC of Induction Motor Based On Particle Swarm Optimization, Genetic Algorithm and Fuzzy Logic. i-manager’s Journal on Electrical Engineering, 2(2), Oct-Dec 2008, Print ISSN 0973-8835, E-ISSN 2230-7176, pp. 31-37. https://doi.org/10.26634/jee.2.2.307

References

[1] . S.Rajasekaran and G.A.Vijayalakshmi Pai, "Neural Nelworks, Fuzzy Logic and Genetic Algorithm-Synthesis andAppllcatlons", PHI, New Delhi, 2004
[2] . A. E. Fitzgerald, et al., "Electric Machinery", 6th Ed., McGraw-Hill, New York, 2002.
[3] . B. K. Bose, "Power Electronics and AC Drives", Prentice- Hall, Englewood Cliffs, NJ. 1986.
[4] . V.Chitra and R.S.Prabhakar, "Induction Motor speed control using Fuzzy Logic Controller", Transactions of Engineering, Computing and Technology. Vol.17. December 2006. ISSN 1305-5313
[5] . L. Mokrani and K. Kouzi, "Influence of fuzzy adapted scaling factors on the performance of a Fuzzy logic controller based on an indirect vector control for induction motor drive". Journal of Electrical Engineering, Vol.55, No. 7-8,2004, pp. 188-194.
[6] . Shady M.Gadoue, D.Giaouris and J.W.Finch, "Tuning of PI Speed Controller In DTC of Induction Motor Based on Genetic Algorithms and Fuzzy Logic Schemes", University of Newcastle, School of Electrical, Electronic and Computer Engineering
[7] . Zhen-Yu Zhao, Masayoshi Tomizuka and Satoru Isaka, "Fuzzy Gain Scheduling of PID Controllers", IEEE Transactions on Systems, Man, and Cybernetics. Vol. 23, No. 5. September/October 1993
[8] . Kennedy and R. Eberhart, "Particle swarm optimization" in Proc. IEEE Int. Conf. Neural Networks (ICNN'95), Vol. IV, Perth, Australia, ppl 942-1948,1995
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