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Modeling of Alternating Current Motor Performance for Increased Production Using Fuzzy Logic Controller

The low productivity experienced in our industries is as a result of not imbibing intelligence in its production mechanism. We know that induction motors are reliable, robust and with good operating characteristics. A means of starting, regulating and controlling operating parameters are very necessary to improve motor efficiency. This low productivity witnessed in our brewery industry is surmounted by modeling of alternating current (a.c) motor performance for increased production output using fuzzy logic controller. To achieve this it is done in this manner, characterizing and modeling a conventional AC motor so as to establish its operational features while working on variable frequency drive (VFD) control model with known production output, designing a rule base for the use of fuzzy controller for a stable and improved production output of AC motor and designing SIMULINK model for the performance of AC motor under operational condition for an increased output using fuzzy controller for a brewery industry. The results obtained are the highest conventional quantity of bottles of beer produced was 3240 while that of fuzzy controller was 3245 at a stable time of 4 through 10 seconds. With these results obtained, it shows there is an improvement in the production capacity in brewery industry when fuzzy controller is incorporated in the system.

Modeling, Alternating Current, Motor, Increase Production, Fuzzy Controller

APA Style

Ngang Bassey Ngang, Bakare Kazeem, Ugwu Kevin Ikechukwu, Aneke Nnamere Ezekiel. (2021). Modeling of Alternating Current Motor Performance for Increased Production Using Fuzzy Logic Controller. International Journal of Electrical Components and Energy Conversion, 7(1), 17-22.

ACS Style

Ngang Bassey Ngang; Bakare Kazeem; Ugwu Kevin Ikechukwu; Aneke Nnamere Ezekiel. Modeling of Alternating Current Motor Performance for Increased Production Using Fuzzy Logic Controller. Int. J. Electr. Compon. Energy Convers. 2021, 7(1), 17-22. doi: 10.11648/j.ijecec.20210701.13

AMA Style

Ngang Bassey Ngang, Bakare Kazeem, Ugwu Kevin Ikechukwu, Aneke Nnamere Ezekiel. Modeling of Alternating Current Motor Performance for Increased Production Using Fuzzy Logic Controller. Int J Electr Compon Energy Convers. 2021;7(1):17-22. doi: 10.11648/j.ijecec.20210701.13

Copyright © 2021 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License ( which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

1. Adrienn Dineva 1 and Amir Mosavi (2019). Review of Soft Computing Models in Design and Control of Rotating Electrical Machine. Energies 2019, 12, 1049; doi: 10.3390/en12061049.
2. Kouki Matsuse and Daiki Matsuhashi (2017): New Technical Trends on Adjustable Speed AC Motor Drives; Chinese Journal of Electrical Engineering, Vol. 3, No. 1, June 2017.
3. M H. Mohammadi, R. C. P. and Silva, D. A Lowther,. (2018).”Incorporating Control Strategies Into the Optimization of Synchronous AC Machines: A comparison of Methodologies”, IEEE Transaction on magnetics, vol. 54, no. 3.
4. K. B. Ravindrakumar, K. Karthick and D. Sivanandakumar (2019). Fuzzy Based Approach for Direct Torque Control Of Three Phase Induction Motor. International Journal of Scientific & Technology Research Volume 8, Issue 10.
5. Maria Drakaki, Yannis L. Karnavas, Athanasios D. Karlis, Ioannis D. Chasiotis and Panagiotis Tzionas (2019): Study on Fault Diagnosis of Broken Rotor Bars in Squirrel Cage Induction Motors: A Multi-Agent System Approach Using Intelligent Classifiers; IET Electric Power Applications.
6. Uma Sabareesh, V & Karthick, K 2019, ‗Solar PV based Permanent Magnet Synchronous Motor Drive for Water Pumping Application‘, International Journal of Innovative Technology and Exploring Engineering (IJITEE), Blue Eyes Intelligence Engineering & Sciences Publication, Vol. 8, No. 9, pp. 837-843.
7. S. M. Tripathi and R. Vaish,(2019). "Taxonomic research survey on vector controlled induction motor drives," in IET Power Electronics, vol. 12, no. 7, pp. 1603-1615, 19 6.
8. M. R. Barusu, U. Sethurajan and M. Deivasigamani, (2019). "Noninvasive method for rotor bar fault diagnosis in three-phase squirrel cage induction motor with advanced signal processing technique," in The Journal of Engineering, vol. 2019, no. 17, pp. 4415-4419, 6 2019.
9. N. B. b. Ahamad, C. Su, X. Zhaoxia, J. C. (2019). "Energy Harvesting From Harbor Cranes with Flywheel Energy Storage Systems," in IEEE Transactions on Industry Applications, vol. 55, no. 4, pp. 3354-3364.
10. M. K. Metwaly, H. Z. Azazi, and S. A. Deraz,(2019) "Power Factor Correction of Three-Phase PWM AC Chopper Fed Induction Motor Drive System Using HBCC Technique," in IEEE Access, vol. 7, pp. 43438-43452.
11. F. Khammar and N. E. Debbache (2016): Application of Artificial Intelligence Techniques for the Control of the Asynchronous Machine; Journal of Electrical and Computer Engineering Volume 2016, Article ID 8052027, 11 pages.
12. Munira Batool and Aftab Ahmad (2013): Mathematical Modeling and Speed Torque Analysis of Three Phase Squirrel Cage Induction Motor Using MATLAB Simulink for Electrical Machines Laboratory; International Electrical Engineering Journal (IEEJ) Vol. 4 (2013) No. 1, pp. 880-889.
13. Jithin J, K R Devika, Jasim Ali M and Krishnenedhu Murali (2019): Speed and Torque Control of 3 Phase Induction Motors using Periferal Interface Controller; International Journal of Research Studies in Electrical and Electronics Engineering (IJRSEEE) Volume 5, Issue 3, 2019, PP 1-4.
14. Jinjie Huang, Shiyong Li, Chuntao Man. (2003). A TS type of fuzzy controller based on process of input output data”, Proc. of 42nd IEEE Conf. on Decision & Control (CDC’03), Hawai, USA, pp. 4729-4734.
15. Mouloud Azzedine Denai, Sid Ahmed Atti. (2002). “Fuzzy and Neural Control of an Induction Motor”, Proc. Int. J. Appl. Math. Comput. Sci., Vol. 12, No. 2, pp. 221–233.
16. H Hartono and Sudjoko, R. I (2019) Journal of Physics Conference. Series. 1381 012053.
17. Ngang N. B. (2020). Hydro power Generator speed control using Fuzzy software Tool. International Journal of Emerging Trends in Engineering and Development (IJETED) Vol. 3, No. 10, DOI: