  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 Levys
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
