The particle swarm optimization (PSO) algorithm is a kind of optimization method based on the theory of cluster intelligence. The greatest advantage of PSO algorithm is its fast convergence speed, simplicity of evolution operation, low computational cost and few parameters needed.
Kim Yong Su, a researcher at the Faculty of Automatics, proposed a method of designing a PID controller using the PSO algorithm and the dominant pole placement.
He used the PSO algorithm to determine the position of dominant pole for minimizing the judge function consisting of the absolute error integral index (IAE) and overshoot value, and used Fuzzy Neural Network (FNN) to determine the parameters of PID controller.
The proposed method makes it possible to get both the optimal dominant pole and the exchanging frequency at the same time and to get good control results as the overshoot value is small. The simulation results demonstrated that the proposed method is effective.
For more information, you can refer to his paper “Self-Tuning Method of PID Controller using PSO and Fuzzy Neural Network” in “Proceedings of KUTIC-2025”.