Particle swarm optimization based PID controller design

From past to present, the main subject of all industrial applications has been to control and/or control systems. In this respect, traditional PID control has taken its place among the frequently used controllers. It is known that the optimum adjustment of PID control parameters increases the profitability of the systems. However, deterioration and/or changes in the systems require re-adjustment of these parameters. It is known that different methods such as intelligent, expert, intuitive, etc. are used in the determination of parameters and studies on this subject are still up-to-date. In this study, Particle Swarm Optimization (PSO) technique was used to determine PID control parameters. PSO is preferred because of its advantages such as ease of application, fast convergence, and no need for complex equations. In this study, PSO-based PID design was carried out, and the parameters of all variations (P, PI, PD, and PID) of the PID controller were determined by the PSO technique. Six different error signals were used to evaluate the performance of the PSO. The performance of all controllers with error signal types applied to the PSO algorithm has been examined and analyzed. The whole simulation of the study was made in Matlab software and the results were analyzed by presenting them in graphics.