Brushless Motor Performance Optimization by Eagle Strategy with Firefly and PSO

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
  
© 2020 by IJETT Journal
Volume-68 Issue-9
Year of Publication : 2020
Authors : Appalabathula Venkatesh, Pradeepa H, Chidanandappa R, Shankar Nalinakshan, Jayasankar V N
DOI :  10.14445/22315381/IJETT-V68I9P220

Citation 

MLA Style: Appalabathula Venkatesh, Pradeepa H, Chidanandappa R, Shankar Nalinakshan, Jayasankar V N  "Brushless Motor Performance Optimization by Eagle Strategy with Firefly and PSO" International Journal of Engineering Trends and Technology 68.9(2020):146-153. 

APA Style:Appalabathula Venkatesh, Pradeepa H, Chidanandappa R, Shankar Nalinakshan, Jayasankar V N. Brushless Motor Performance Optimization by Eagle Strategy with Firefly and PSO  International Journal of Engineering Trends and Technology, 68(9),146-153.

Abstract
Brushless motors has special place though different motors are available because of its special features like absence in commutation, reduced noise and longer lifetime etc., The experimental parameter tracking of BLDC Motor can be achieved by developing a Reference system and their stability is guaranteed by adopting Lyapunov Stability theorems. But the stability is guaranteed only if the adaptive system is incorporated with the powerful and efficient optimization techniques. In this paper the powerful eagle strategy with Particle Swarm optimization and Firefly algorithms are applied to evaluate the performance of brushless motor Where, Eagle Strategy(ES) with the use of Levy’s walk distribution function performs diversified global search and the Particle Swarm Optimization (PSO) and Firefly Algorithm(FFA) performs the efficient intensive local search. The combined operation makes the overall optimization technique as much convenient The simulation results are obtained by using MATLAB Simulink software.

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Keywords
Optimization, Eagle Strategy, Adaptive System, PSO, FFA, Lyapunov Theorems.