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IJMLC 2012 Vol.2(2): 131-137 ISSN: 2010-3700
DOI: 10.7763/IJMLC.2012.V2.101

Efficacy of Different Rule Based Fuzzy Logic Controllers for Induction Motor Drive

B. Kumar, Yogesh K. Chauhan, and V. Shrivastava

Abstract—Performance of an electric drive is paramount for crucial motion applications and greatly influenced by the controller capabilities. Vector control technique is normally applied with the induction motor drive for high performance applications. For such applications fuzzy logic controller (FLC) has been widely used instead of conventional PID controller. However, size of rule-base of FLC is directly influencing the real time computational burden, which subsequently restricts its application with the processors of limited speed & memory. The number of rule base and performance of drive are inversely related with each other as it is evident that all the rules don’t participate equally in the response and can be reduced for simplicity which utilizing less computational resources. In this paper the performance of vector controlled induction motor drive is presented for three different FLC rule bases namely 49, 25 and 9 rules. The drive performance has been investigated for these cases for speed control, disturbance rejection control ability. Moreover, sensitivity of the drive is evaluated for stator resistance control. The performance of drive system using larger FLC rule base is found superior as compared to the performance with lesser rules at the cost of large computational resources and speed.

Index Terms—Fuzzy logic controller, high performance drive, Induction motor, vector control.

Authors are with the School of Engineering, Gautam Buddha University, Greater Noida, 201310, U.P., India (e-mail: kumar_bhavnesh@yahoo.co.in; chauhanyk@yahoo.com; shvivek@gmail.com respectively).

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Cite: B. Kumar, Yogesh K. Chauhan, and V. Shrivastava, "Efficacy of Different Rule Based Fuzzy Logic Controllers for Induction Motor Drive," International Journal of Machine Learning and Computing vol. 2, no. 2, pp. 131-137, 2012.

General Information

  • E-ISSN: 2972-368X
  • Abbreviated Title: Int. J. Mach. Learn.
  • Frequency: Quaterly
  • DOI: 10.18178/IJML
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • Abstracing/Indexing: Inspec (IET), Google Scholar, Crossref, ProQuest, Electronic Journals LibraryCNKI.
  • E-mail: ijml@ejournal.net


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