Brushless Motor Performance Optimization by Eagle Strategy with Firefly and PSO
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.
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.
 Subhash Challa, Mark R. Morelande, Darko Muscki, Robin J. Evans. “Fundamentals Of Object Tracking,” 1st ed., Cambridge University Press, New York: 2011.
 H. J. Jin, J. M. Hwang, and J. M. Lee, “A balancing control strategy for a one wheel pendulum robot based on dynamic model decomposition: simulation and experiments,” IEEE/ASME Trans. On Mechatronics, vol. 16, no. 4, pp. 763-768, 2011.
 C. C. Tsai, H. C. Huang, and S. C. Lin, “Adaptive neural network control of self-balancing two-wheeled scooter,” IEEE Trans. on Industrial Electronics, vol. 57, no. 4, pp. 1420-1428, 2010.
 TJE Miller, “Brushless Permanent-Magnet and Reluctance Motor Drives”, Oxford Science Publications:1989.
 C. H. Huang, W. J. Wang, and C. H. Chiu, “Design and implementation of fuzzy control on a two-wheel inverted pendulum system,” IEEE Trans. on Industrial Electronics, vol. 58, no. 7, pp. 2988-3001, 2011.
 V. Amerongen and J. Intelligent, “Control (Part 1)-MRAS, lecture notes,” University of Twente, The Netherlands, March 2004.
 Appalabathula Venkatesh, Dr. G. Raja Rao, “ An Improved Adaptive Control System for a Two-Wheel Inverted Pendulum-Mobile Robot using Eagle Strategy with a Particle Swarm Optimization,” Journal of Emerging Technologies and Innovative Research, vol. 5,issue 7, July.2018.
 Hamza Yapici, Nurettin Cetinkaya, “An Improved Particle Swarm Optimization Algorithm Using Eagle Strategy for Power Loss Minimization” Mathematical Problems in Engineering, vol. 2017.
 N. D. Cuong, N. Van Lanh, and D. Van Huyen, “Design of MRAS-based adaptive control systems,” in Proc. IEEE 2013 International Conference on Control, Automation and Information Sciences, pp. 79-84, 2013.
 Derek Atherton, “An Introduction to Non-Linearity in Control System”: 2011.
 Nguyen Duy Cuong and Gia Thi Dinh and Tran Xuan Minh, “Direct MRAS Based an Adaptive Control System for a Two-Wheel Mobile Robot” Journal of Automation and Control Engineering ,Vol.3,No.3, June 2015.
 Xin-She Yang, Suash Deb, “Eagle Strategy Using Levy walk and Firefly Algorithms for Stochastic Optimization” Natures Inspired Coorperative Strategies for Optimization (NICSO 2010), pp. 101-111: 2010.
 Appalabathula Venkatesh, Shankar Nalinakshan, S S Kiran, Pradeepa H, “Energy transmission control for a Grid connected modern power system Non-Linear loads with a Series Multi-Stage Transformer Voltage Reinjection with controlled converters” International Journal of Engineering Trends and Technology, Vol. 68,Issue 8, August 2020.
Optimization, Eagle Strategy, Adaptive System, PSO, FFA, Lyapunov Theorems.