PID controller tuning using evolutionary programming

The evolutionary programming algorithm for PID controller tuning presented offers several advantages. One can use a high-order process model in the tuning, and the errors resulting from model reduction are avoided. It is possible to consider several design criteria in a balanced and unified way. Approximations that are typical to classical tuning rules are not needed. Evolutionary programming is often criticized for two reasons: algorithms are computationally heavy and convergence to the optimal solution can not be guaranteed. PID controller tuning is a small-scale problem, and thus computational complexity is not really an issue here. The optimization problem is defined in the paper in such way that convergence is not a problem. We are not looking for an exact solution to a complex optimization problem but instead we are looking for a group of acceptable solutions to a more loosely defined problem. Good initial values provided by some classical tuning rules also help the algorithm to find acceptable solutions rather easily