Speed Control Of Induction Motor Using Fuzzy Logic Controller

Prashant Menghal*, A. Jaya Laxmi**, D. Anusha***
* Faculty of Degree Engineering, Military College of Electronics & Mechanical Engineering, Secunderabad, Telangana and Research Scholar, EEE Department., JNTU, Andhra Pradesh, India.
** Professor, Department of EEE, Jawaharlal Nehru Technological University, College of Engineering, Kukatpally, Hyderabad, Telangana, India.
*** Research Scholar, Department of EEE, Jawaharlal Nehru Technological University, College of Engineering,Kukatpally, Hyderabad, Telangana, India.
Periodicity:October - December'2014
DOI : https://doi.org/10.26634/jee.8.2.3041

Abstract

The use of Induction motors has increased tremendously, since the day of its invention. They are being used as actuators in various industrial processes, robotics, house appliances and other similar applications. The reason for increasing popularity day by day can be primarily attributed to its robust construction, simplicity in design and cost of effectiveness. This paper presents a methodology for implementation of a rule-based fuzzy logic controller applied to a closed loop Volts/Hz speed control of induction motor. The Induction motor is modelled using a dq axis theory. The designed Fuzzy Logic Controller's performance is weighed and is compared with that of a PI controller. The system has been simulated in MATLAB/SIMULINK and the results have been presented. The results obtained by using a conventional PI controller and the designed Fuzzy Logic Controller have been compared.

Keywords

v/f Speed Control, dq Axis Theory, Fuzzy Logic Controller (FLC), Mamdani Architecture, Graphical user Interface (GUI)

How to Cite this Article?

Menghal, P. M. Laxmi, A. J., and Anusha, D. (2014). Speed Control Of Induction Motor Using Fuzzy Logic Controller. i-manager’s Journal on Electrical Engineering , 8(2), 21-31. https://doi.org/10.26634/jee.8.2.3041

References

[1]. Tze Fun Chan., Keli Shi (2011). “Applied Intelligent Control of Induction Motor Drives”. IEEE Willey Press.
[2]. P.C. Krause (2000). Analysis of Electrical Machinery and Drives System. IEEE Willey Press.
[3]. Ned Mohan (2001). Advanced Electric Drives: Analysis, Control Modeling using Simulink. MNPERE Publication.
[4]. K.L.Shi, T.F.Chan, Y. K. Wong and S. L .HO (1999). Modeling and simulation of the three phase induction motor Using SIMULINK. Int.J. Elect. Engg. Educ, Vol. 36, pp. 163–172. doi. 10.1109/IEMDC.1997.604326.
[5]. P. M.Menghal, A Jaya Laxmi and N.Mukhesh (2014). Dynamic Simulation of Induction Motor Drive using Artificial I n tel l i gen t Con trol l er. I EEE I n t. Con f. . Con trol , Instrumentation, Energy and Communication (CIEC), pp.301-305. doi: 10.1109/CIEC.2014.6959098.
[6]. P.M Menghal, and A Jaya Laxmi (2014). “Neural Network Based Dynamic Performance of Induction Motor Drives. Springer Journal of Advances in Intelligent Systems and Computing, Vol. 259, pp. 539-551. doi: 10.1007/978- 81-322-1768-8_48.
[7]. P M Menghal, and A Jaya Laxmi (2014). “Dynamic Performance of Induction Motor Drive Using Hybrid Controller. Journal of Automation & Systems Engineering Vol.8-1, Pp. 40-50.
[8]. P. M. Menghal and Dr. A. Jaya Laxmi (2014). “Artificial Intelligent Control of Induction Motor Drives”. i-manager's Journal on Instrumentation and Control Engineering, 2(1), Nov-Jan, 2014, Print ISSN 2321-113X, E-ISSN 2321-1148, pp. 9-22.
[9]. P M Menghal, and A.Jaya Laxmi (2012). “Artificial Intelligence Based Dynamic Simulation of Induction Motor Drives”. IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE), Vol.3(5), 37-45.doi: 10.9790/ 1676-0353745.
[10]. P M Menghal, and A. Jaya Laxmi (2013). “Adaptive Neuro Fuzzy based Dynamic Simulation of Induction Motor Drives”. IEEE Int. conf. Fuzzy Systems, 1-8.doi:10.1109/FUZZIEEE. 2013.6622452.
[11]. P M Menghal, and A Jaya Laxmi (2013). Neural Network based Dynamic Simulation of Induction Motor Drives. IEEE Int. conf. Power, Energy & Control,566-571.doi :10.1109/ICPEC.2013.6527722.
[12]. P M .Menghal, and A Jaya Laxmi (2012). Adaptive Neuro Fuzzy Interference (ANFIS) based simulation of Induction motor drive. Int. Review on Modeling and Simulation (IRMOS), 5(5), 2007-2016.
[13]. M. Nasir Uddin, and Muhammad Hafeez (2012). FLCBased DTC Scheme to Improve the Dynamic Performance of an IM Drive. IEEE Trans. Ind. Appl, 823-831.doi: 10.1109/TIA.2011.2181287.
[14]. M. Nasir Uddin, and Hao Wen (2007). Development of a Self-Tuned Neuro-Fuzzy Controller for Induction Motor Drives. IEEE Trans Ind. App, 1108-1116.doi : 10.1109/TIA.2007.900472.
[15]. M Nasir Uddin, and Tawfik S. Radwan et al. (2002). Performance of Fuzzy logic based indirect vector control for induction motor drive, IEEE Trans. Ind. Appl, Vol. 38(5),1219-1225.doi: 10.1109/TIA.2002.802990.
[16]. Besir Dandil, Muammer Gokbulut Fikrat Ata (2005). A PI Type Fuzzy –Neural Controller for Induction Motor Drives. Journal of Appl. Sci., Vol. 5(7), pp. 1286-1291.doi: 10.3923/jas.2005.
[17]. Rajesh Kumar, R. A. Gupta Rajesh S. Surjuse (2009). “Adaptive Neuro-Fuzzy Speed Controller for Vector Controlled Induction Motor Drive”. Asian Power Electro. Journal, Vol. 3(1), pp. 8-14. doi:14.79e41505757a2a8cab.
[18]. Mouloud Azzedine Denai and Sid Ahmed Attia (2002). Fuzzy and Neural Control of an Induction Motor, Int. J. Appl. Math. Computer. Sci., Vol. 12 (2), pp. 8-14. doi:10.1.1.135.303.
[19]. Bimal K. Bose (2007). Neural Network Applications in Power Electronics and Motor Drives - An Introduction and Perspective. IEEE Trans. Ind. Electronics, Vol. 54(1), pp. 14- 33.doi: 10.1109/TIE.2006.888683.
[20]. Uddin, M.N.,Huang, Z.R. et al (2007). “A Simplified Self- Tuned Neuro-Fuzzy Controller Based Speed Control of an Induction Motor Drive”. IEEE Power Engineering Society General Meeting, Vol. 1-8.doi: 10.1109/PES.2007.385720.
[21]. M Nasir Uddin, Tawfik S. Radwan and Azizur Rahman (2002). Performance Of Fuzzy Logic based Indirect Vector Control for Induction Motor Drive. IEEE Trans on industry application, Vol. 38(5), pp.1219-1225. doi: 10.1109/ IAS.2000.881989.
If you have access to this article please login to view the article or kindly login to purchase the article

Purchase Instant Access

Single Article

North Americas,UK,
Middle East,Europe
India Rest of world
USD EUR INR USD-ROW
Pdf 35 35 200 20
Online 35 35 200 15
Pdf & Online 35 35 400 25

Options for accessing this content:
  • If you would like institutional access to this content, please recommend the title to your librarian.
    Library Recommendation Form
  • If you already have i-manager's user account: Login above and proceed to purchase the article.
  • New Users: Please register, then proceed to purchase the article.