Evolutionary Tuning of Optimal PID Controllers for Second Order Systems Plus Time Delay

PID stands for "proportional, integral, derivative'' The PID controller is the most widely used industrial device for monitoring and controlling processes. Those three elements are the basics of a PID Controller. Each one performs a different task and has a different effect on the functioning of a system. The expected behavior of a system depends of the setting of those parameters. There are alternatives to the traditional rules of PID tuning, but there is not yet a study showing that the use of heuristic algorithms it is indeed better than using classic methods of optimal tuning. This is developed in this paper. An evolutionary algorithm MAGO (Multidynamics Algorithm for Global Optimization) is used to optimize the controller parameters minimizing the ITAE performance index. The procedure is applied to a set of benchmark problems modeled as Second Order Systems Plus Time Delay (SOSPD) plants. The evolutionary approach gets a better overall performance comparing to traditional methods (Bohl and McAvoy, ITAE-Hassan, ITAE-Sung), regardless the plant used and its operating mode (servo or regulator), covering all restrictions of the traditional methods and extending the maximum and minimum boundaries between them.