Design of MFA-PSO based fractional order PID controller for effective torque controlled BLDC motor

Abstract

This paper presents an effective torque and speed regulation strategy for BLDC motor (BLDCM) using Modified Firefly Algorithm (MFA)–Particle Swarm Optimization (PSO) based Fractional Order PID (FOPID) controller. Due to simplicity and better steady state performance, typical PID controllers are used to control the BLDC motors. However, due to load variations, it has an issue with uncertainty. The PID controller tuning also contributes to uncertainty in the parameters of the structure. With the help of the FOPID controller, accurate control method can be provided to overcome the above problems. A combination of MFA and PSO algorithms are employed to tune the FOPID parameters. Simulations of proposed MFA-PSO based FOPID controller for BLDC speed are carrying away in Matlab/Simulink atmosphere. To authenticate the applicability of proposed controller for BLDC motor, the consequences are compared through Genetic Algorithm (GA), Firefly Algorithm (FA) and Firefly-Artificial Neural Network (ANN) based FOPID controllers.