A Fast Firefly Algorithm for Function Optimization: Application to the Control of BLDC Motor
Smail Bazi, Redha Benzid, Yakoub Bazi, Mohamad Mahmoud Al Rahhal
Abstract
Firefly Algorithm (FA) is a recent swarm intelligence first introduced by X.S. Yang in 2008. It has been widely used to solve several optimization problems. Since then, many research works were elaborated presenting modified versions intending to improve performances of the standard one. Consequently, this article aims to present an accelerated variant compared to the original Algorithm. Through the resolving of some benchmark functions to reach optimal solution, obtained results demonstrate the superiority of the suggested alternative, so-called Fast Firefly Algorithm (FFA), when faced with those of the standard FA in term of convergence fastness to the global solution according to an almost similar precision. Additionally, a successful application for the control of a brushless direct current electric motor (BLDC) motor by optimization of the Proportional Integral (PI) regulator parameters is given. These parameters are optimized by the FFA, FA, GA, PSO and ABC algorithms using the IAE, ISE, ITAE and ISTE performance criteria.