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JCR Impact Factor: 0.459
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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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Broken Bar Fault Detection in IM Operating Under No-Load Condition, RELJIC, D., JERKAN, D., MARCETIC, D., OROS, D.
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  1/2011 - 8

Optimal Fuzzy Controller Tuned by TV-PSO for Induction Motor Speed Control

KULIC, F. See more information about KULIC, F. on SCOPUS See more information about KULIC, F. on IEEExplore See more information about KULIC, F. on Web of Science, MATIC, D. See more information about  MATIC, D. on SCOPUS See more information about  MATIC, D. on SCOPUS See more information about MATIC, D. on Web of Science, DUMNIC, B. See more information about  DUMNIC, B. on SCOPUS See more information about  DUMNIC, B. on SCOPUS See more information about DUMNIC, B. on Web of Science, VASIC, V. See more information about VASIC, V. on SCOPUS See more information about VASIC, V. on SCOPUS See more information about VASIC, V. on Web of Science
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Author keywords
fuzzy logic, speed control, proportional-integral controller, swarm particle optimization, induction motor

References keywords
control(11), fuzzy(8), drives(6), controller(6), induction(5), vector(4), tuning(4), speed(4), motor(4), matic(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2011-02-27
Volume 11, Issue 1, Year 2011, On page(s): 49 - 54
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2011.01008
Web of Science Accession Number: 000288761800008
SCOPUS ID: 79955979236

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This paper reports an automated procedure for the design of an optimal fuzzy logic controller to be used as an induction motor speed controller. The procedure consists of selection of a suitable well known fuzzy logic controller and tuning via particle swarm optimization optimal for the selected criteria. In this way the time required for tuning of the controller is significantly reduced in comparison with trial and error methods. As a benchmark a proportional-integral (PI) controller is used. The PI controller is tuned via the symmetrical optimum procedure, the standard procedure for tuning a speed controller of an induction motor. Simulation results are obtained via a mathematical model developed in Matlab/Simulink. Experimental verification is carried out with a laboratory model based on the DS1104 digital control card. To minimize iron losses and to provide better motor performance for low loads, flux is reduced from nominal and speed is kept below nominal. Results are presented in tables and graphics. The optimal fuzzy logic controller provides a slight practical advantage.

References | Cited By  «-- Click to see who has cited this paper

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[2] P. Vas. Sensorless Vector and Direct Torque Control. Oxford University Press, 1988, ISBN 0-19-856465

[3] S. Y. Nof. Handbook of industrial robotics, John Wiley and Sons, Inc., 1999, ISBN 0-471-17783-0

[4] P. Vas. Artificial Intelligence Based Electrical Machines and Drives, Oxford University Press, 1999, ISBN 0-19-859397

[5] R. Eberhart and J. Kennedy, "A new optimizer using particle swarm theory", Proceedings of the Sixth International Symposium on Micro Machine and Human Science, MHS '95, pp.39-43, 4-6 Oct 1995, Nagoya , Japan

[6] M. Rapajic and Z. Kanovic, "Time Varaying PSO - convergence analysis convergence-related parameterization and new parameter adjustment scheme," Information Processing Letters, vol. 109, pp.548-552, January 2009.
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[7] J. W. Umland and M. Safiuddin, "Magnitude and Symmetric Optimum Criterion for the Design of Linear Control System: What Is It and How Does Compare With the Others?," IEEE Transactions of Industry Applications, vol.26, pp.489-497, June 1990.
[CrossRef] [Web of Science Times Cited 33] [SCOPUS Times Cited 47]

[8] I. Birou, V. Maier, S. Pavel, and C. Rusu, "Indirect Vector Control of an Induction Motor with Fuzzy-Logic based Speed Controller," Advances in Electrical and Computer Engineering, vol. 10, pp.116-120, 2010.
[CrossRef] [Full Text] [Web of Science Times Cited 10] [SCOPUS Times Cited 14]

[9] B. Heber, L. Xu, and Y. Tang, "Fuzzy Logic Enhanced Speed Control of an Indirect Field-Oriented Induction Machine Drive," IEEE Transactions of Power Electronics, vol.12, pp.772-778, Sept. 1997.
[CrossRef] [Web of Science Times Cited 53] [SCOPUS Times Cited 90]

[10] M. Masiala, B. Vafakhah, J. Salmon, and A. M. Knight, "Fuzzy Self Tuning Speed Control of an Induction Motor Drive," IEEE Transactions of industry Applications, vol. 44, pp.1732-1740, Dec. 2008.
[CrossRef] [Web of Science Times Cited 44] [SCOPUS Times Cited 66]

[11] S. V. Ustun and M. Demirtas, "Optimal Tuning of PI coefficients by using fuzzy-genetic for V/f controlled induction motor," Expert Systems with Applications vol. 34, pp. 2714-2720, 2008.
[CrossRef] [Web of Science Times Cited 16] [SCOPUS Times Cited 24]

[12] H.N Nounou and H. Rehman, "Application of Adaptive Fuzzy Control to AC Machine," Applied Soft Computing, vol. 7, pp.899-907, 2007.
[CrossRef] [Web of Science Times Cited 21] [SCOPUS Times Cited 26]

[13] Z. Ibrahim and E. Levi, "A Comparative Analysis of Fuzzy Logic and PI Speed Control in High-Performance AC Drives Using Experimental Approach," IEEE Transactions of Industry Applications vol. 38, pp.1210-1218, October 2002.
[CrossRef] [Web of Science Times Cited 55] [SCOPUS Times Cited 80]

[14] D. Matic, F. Kulic, B. Dumnic, and V. Vasic, "Optimal controller design in indirect vector control scheme," Proceedings of Eighteenth Electrotechnical and Computer Science Conference ERK 2009 IEEE Region 8, pp. 235-238, 21-23 September, Portoroz, Slovenia, 2009, ISBN 1581-4572

[15] K. J. Astrom and T. Hagglund, PID Controllers, Theory, Design and Tuning 2nd edition, Instrument Society of America, 1995, ISBN 1-55617-516-7

[16] B. Jeftenic, V.Vasic, and D. Oros, Regulated electrical drives, Akademska misao Beograd, 2004, ISBN 86-7466-158-0, published in Serbian

[17] F. Kulic, D. Matic, V. Vasic, and D. Oros, "Tuning of PI Controller Parameters For The Control of Absorption Oil Temperature In Process of Vegetable Oil Production," Journal on Processing and Energy in Agriculture, vol.3, pp.93-98, Nov. 2007.

[18] K. Laroussi, M. Zelmat, and M. Rouff "Implementation of Fuzzy Logic System to Tune PI Controller Applied to an Induction Motor", Advances in Electrical and Computer Engineering, vol. 9, pp.107-113, 2009.
[CrossRef] [Full Text] [Web of Science Times Cited 5] [SCOPUS Times Cited 5]

[19] D. Matic, B. Dumnic, F. Kulic, and V. Vasic, "Minimal Configuration PI Fuyyz Gain Scheduling Controller in Indirect Vector Control Scheme," The 5th IET International Conference on Power Electronics, Machines and Drives, 19-21 April, Brighton, United Kingdom, 2010.

[20] D. Matic, V. Bugarski, F. Kulic, and Z. Jeličic, "One realization of fuzzy controller for electric drives" Regional conference Industrial energetic and environmental protection in countries of Southeast Europe IEEP 2008, 24-27. Jun 2008. Zlatibor, Serbia.

References Weight

Web of Science® Citations for all references: 260 TCR
SCOPUS® Citations for all references: 381 TCR

Web of Science® Average Citations per reference: 13 ACR
SCOPUS® Average Citations per reference: 19 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

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