Optimal Tuning of PID Controller Using Genetic Algorithm and Swarm Techniques

In order to control the systems, a few control strategies must deal with the effects of non-linearties or uncertainties. As earlier utilized control techniques based on mathematical models have been primarily concentrated on stability robustness against the ill-effects of control mechanism, they are limited in their ability to amend the transient responses. These conventional techniques failed to tune the non-linear and non-minimum phase systems. Therefore, a few modern algorithms have been introduced here such as; Bacteria Foraging Optimization, Particle Swarm Optimization and Genetic Algorithm which have been proved an appropriate aid to improve the transient responses of systems perturbed by non-linearties or unknown mathematical characteristics. This Paper presents designing a PID controller by selection of PID parameters using Bacterial Foraging Optimization, Particle Swarm Optimization (PSO) and Genetic Algorithm. Here, the closed loop step response of the PID controller has been compared for the above mentioned three optimization algorithms.