Fractional-order PID control of a chopper-fed DC motor drive using a novel firefly algorithm with dynamic control mechanism

Abstract

In this paper, a dynamic control mechanism is proposed to improve the firefly algorithm's (FA) rate of convergence and minimization of the fitness function. The dynamic FA (DFA) dynamically selects the best-performing combinations of the step size scaling factor, the attractiveness coefficient, the absorption coefficient and the population size along the complete evolution process of the algorithm. A fractional-order PID (FOPID) controller based on DFA is proposed to improve the performance of a chopper-fed direct current motor drive. The proposed controller is used in speed control loop to improve the response. To illustrate the efficacy of the DFA-based FOPID, we compare its performance with those based on the conventional FA, genetic algorithm, particle swarm optimization, artificial bee colony algorithm and differential evolution algorithm. The simulation results and analyses show the effectiveness of the proposed method.