Google Scholar

##plugins.themes.academic_pro.article.sidebar##

Published
Jan 19, 2015
Download
PDF
Statistic
Read Counter : 38 Download : 30

Downloads

Download data is not yet available.

##plugins.themes.academic_pro.article.main##

Abstract

Efficiency optimization of motor drives is very important not only from the viewpoints of energy loss and hence cost saving, but also from the perspective of environmental pollution. Several efficiency optimization methods for induction motor (IM) drives have been introduced nowadays by researchers. Distinctively, artificial intelligence (AI)-based techniques, in particular Fuzzy Logic (FL) one, have been emerged as a powerful alternative to conventional methods. Design objectives that are mathematically hard to express can be incorporated into a Fuzzy Logic Controller (FLC) using simple linguistic terms. The merit of FLC relies on its ability to express the amount of ambiguity in human reasoning. When the mathematical model of a process does not exist or exists with uncertainties, FLC has proven to be one of the best alternatives to move with unknown process.

In this paper, an implementation of intelligent controller for speed control of an induction motor (IM) using indirect vector control method has been developed and analyzed in detail. The project is complete mathematical model of field orientation control (FOC) of induction motor and simulated in MATLAB for studies of a 50 HP, squirrel cage type induction motor has been considered. The comparative performance of Fuzzy Logic control technique has been presented and analyzed in this work. The present approach avoids the use of flux and speed sensor which increase the installation cost and mechanical robustness. The fuzzy logic controller is found to be a very useful technique to obtain a high performance speed control. The indirect vector controlled induction motor drive involves decoupling of the stator current in to torque and flux producing components.

Keywords:  Induction motor(IM) drive,  Indirect Vector Control of Induction Motor(IVCIM),  Fuzzy Logic Controller(FLC),Field Oriented Control(FOC), Matlab,Fuzzy Inference System(FIS), Simulink model

##plugins.themes.academic_pro.article.details##

Author Biographies

Lakhya Jyoti Phukon, Jorhat Engineering College, Jorhat 785007, Assam

M.E. (2nd year), Electrical Engineering (Instrumentation & Control),

Dr. Neelanjana Baruah, Jorhat Engineering College, Jorhat 785007, Assam

2Associate Professor, Department of Electrical & Instrumentation Engineering
How to Cite
Phukon, L. J., & Baruah, D. N. (2015). Fuzzy Logic based Speed Control of an Induction Motor Using Indirect Vector Control Method. International Journal of Emerging Trends in Science and Technology, 2(01). Retrieved from http://igmpublication.org/ijetst.in/index.php/ijetst/article/view/466

References

[1] Gopal K. Dubey, “Fundamental of Electrical Drives”, Narosa Publication House, Second Edition, 2011
[2] R. Krishnan, “Electric Motor Drives-modeling, analysis and control”, Pearson education
[3] Bimal K.Bose, “Modern Power Electronics and AC Drives”, Pearson education
[4] W. Leonhard, “Field-orientation for controlling a.c. machines – Principle and application”, in Proc. of the 3rd International Conference on Power Electronics and Variable Speed Drives, London, pp. 277-282, IEEE, 1988
[5] Anuradha Tomar and Yog Raj “Various Control Techniques for Induction Motor Drive: A Brief Insight” IJERT; Vol. 1 Issue 5, July – 2012.
[6] N. Mohan, “Advanced Electric Drives: Analysis, Control and Modeling using Simulink®,” Minnesota Power Elec-tronics Research & Education, Minnesota, 2001.
[7] Thomas A. Lipo, & Donald W. Novotny, “A New Induction Motor V/f Control Method Capable of High-Performance Regulation at Low Speeds” IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, VOL. 34, NO. 4, JULY/AUGUST 1998.
[8] S. V. Zadeh and E.Jalali “Combined vector control and direct torque control method for high performance induction motor drives,”, Science Direct, Energy Conversion and Management, vol 48, pp 3095-3101, 2007.
[9] M. N. Uddin, T. S. Radwan, and M. A. Rahman, “Performances of Fuzzy-Logic-Based Indirect Vector Control for Induction Motor Drive”, IEEE Transactions On Industry Applications, Vol. 38, No. 5, pp. 1219-1225, Sept./Oct. 2002.
[10] L.A. Zadeh,”fuzzy theory,” university of California, Berkely, 1965
[11] P.Tripura and Y.Srinivasa Kishore Babu ― “Fuzzy Logic Speed Control of Three Phase Induction Motor Drive”, World Academy of Science, Engineering and Technology 60 ,2011
[12] George J. Klir/Bo Yuan, Fuzzy Sets and Fuzzy Logic (New Delhi: Prentice-Hall of India Private Limited, 2005).
[13] Ashutosh Mishra and Prashant Choudhary" Speed Control of an Induction Motor by Using Indirect Vector Control Method "www.ijetae.com (ISSN 2250 2459, ISO9001:2008 Certified Journal, Volume 2, Issue 12, and December 2012)
[14] Ashok Kusagur, S.F.Kodad, B.V. Sankar Ram, “Novel design of a Takagi-Sugeno fuzzy strategy for induction motor speed control”,Paper accepted for publication in Journal of Electrical Systems, Vol. 6, issue 2, Jun. 2010.
15] Mir. S.A and Malik. E. Elbuluk, “Fuzzy controller for Inverter fed Induction Machines”, IEEE Transactions on Industry Applications, Vol. 30, pp. 78-84, 1994.
[16] L.Zhen and L.Xu, “Fuzzy learning enhanced speed control of an indirected field-oriented induction machine drives,”IEEE Trans.Control S System Technology, Vol-8, no-2, pp.270 278, March2000.
[17] MATLAB/SIMULINK® version 2011a, the MathWorks Inc., USA
[18] Fuzzy Inference Systems reference manual for MATLAB/ SIMULINK® version 2011a.