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Research Article Open access CC BY 4.0

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 · pp. 54–64 · Published 11 May 2020

10.9734/cjast/2020/v39i930606

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.

Brushless DC motor genetic algorithm back EMF fuzzy knowledge base controller

Cited by 4

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Nikkitha K, Sowmya E, Parimala E · 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) · 2022

Fault Detection and Torque Control in BLDC Motor using AI

Karthikeyan Kaliyaperumal, T. Sathesh Kumar, Ravi Kant · 2022 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES) · 2022

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