SOSPD Controllers Tuning by Means of an Evolutionary Algorithm

Abstract

The Proportional Integral Derivative (PID) controller is the most widely used industrial device to monitoring and controlling processes. There are numerous methods for estimating the controller parameters, in general, resolving particular cases. Current trends in parameter estimation minimize an integral performance criterion. Therefore, the calculation of the controller parameters is proposed as an optimization problem. Although there are alternatives to the traditional rules of tuning, there is not yet a study showing that the use of heuristic algorithms it is indeed better than using the classic methods of optimal tuning. In this paper, the evolutionary algorithm MAGO is used as a tool to optimize the controller parameters. The procedure is applied to a range of standard plants modeled as a Second Order System plus Time Delay. Better results than traditional methods of optimal tuning, regardless of the operating mode of the controller, are yielded.