PSO and PSO-BFO Based Tuning of PID Controller: A Comparative Evaluation

Abstract— The aim of this paper is to study the tuning of a PID controller using swarm optimization techniques. In this paper, comparative performance of PSO and BF-PSO based PID controller is analyzed. PSO algorithm converges rapidly during the initial stages of a global search, but around global optimum, the search process slows down. In order to overcome this problem and to further enhance the performance of PSO, this paper implements a hybrid algorithm (BF-PSO) combining the features of Bacterial Foraging Optimization (BFO) and Particle Swarm Optimization (PSO) for tuning of PID controller. The simulation results show that the hybrid (BF-PSO) algorithm has less settling time and less overshoot than PSO algorithm. BF-PSO algorithm is better than Z-N tuning method and PSO in terms of set point tracking, simplicity, consistency, search and computational efficiency.