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Speed Control of Brushless DC Motor Using Modified Genetic Algorithm Tuned Fuzzy Controller

  • Ankit Rawat
  • Mohd Fazle Azeem

Current Journal of Applied Science and Technology, Page 54-64
DOI: 10.9734/cjast/2020/v39i930606
Published: 11 May 2020

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Abstract


In the last decade with increasing motor application domain, need towards usage of precisely controlled, noise free, highly efficient and high starting torque motors also increases, as a result dedicated applications has fascinated the researcher toward brushless DC motor. Brushless DC motors can act as suitable alternative to the traditional Brushed direct current motor, Induction Motor etc. This research paper inspects the ease and effectiveness of modified queen bee based GA tuned fuzzy controller and shows the performance of a proposed controller under diverse speed settings. A comparative study with conventional PI controller shows effectiveness of modified queen bee based GA Tuned Fuzzy controller, in terms of parameter like peak overshoot and settling time. MATLAB/SIMULINK Environment is used for optimization and modeling of Brushless DC motor drive.


Keywords:
  • Brushless DC motor
  • genetic algorithm
  • back EMF
  • fuzzy knowledge base controller
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  • Review History

How to Cite

Rawat, A., & Azeem, M. F. (2020). Speed Control of Brushless DC Motor Using Modified Genetic Algorithm Tuned Fuzzy Controller. Current Journal of Applied Science and Technology, 39(9), 54-64. https://doi.org/10.9734/cjast/2020/v39i930606
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References

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Mondal S, Mitra A, Chattopadhyay M. Mathematical modeling and simulation of Brushless DC motor with ideal Back EMF for a precision speed control, 2015 IEEE International Conference on Electrical, Computer and Communication Techno-logies (ICECCT), Coimbatore. 2015;1-5.
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Rawat A, Azeem MF. Performance analysis of brushless DC motor using modified queen bee evolution based genetic algorithm tuned PI controller under different speed conditions. Advances in Research. 2020;1-10.

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[Online No.20030383]
DOI: 10.1049/el: 20030383
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