Tuning a PID controller using particle swarm optimization (PSO)

Abstract

The aim of this project is to tune a PID controller using artificial intelligence. The standard gain tuning of PID controllers such as Ziegler-Nichols, Coheen-Coon etc… tend to present big overshoots, and therefore artificial intelligence approach such as ant colony optimization and genetic algorithms are more adopted to enhance the results of standard techniques. However, due to computational efficiency, the main focus will be on the particle swarm optimization method (PSO). A comparison between PID and PSO versus PID and ZN (Ziegler-Nichols) will be represented where the results will show the advantage of PSO in PID tuning.