Tuning of Optimal Classical and Fractional Order PID Parameters for Automatic Generation Control Based on the Bacterial Swarm Optimization

Abstract

Particle Swarm Optimization algorithm converges rapidly during the initial stage 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 Particle Swarm Optimization, this paper implements a hybrid algorithm, Bacterial Swarm Optimization, combining the features of Bacterial Foraging Optimization and Particle Swarm Optimization. The PID parameters of classical and fractional-order controllers are optimized with Bacterial Swarm Optimization for load frequency control of a two area power system. Simulation results show fractional-order PID controller has less settling time and less overshoot than the classical PID controller for most of studies. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.