A COMBINATION OF SCALABLE ALGORITHMS FOR OPTIMISING PI CONTROLLER

Abstract

In several works using a single approach for optimization the parametres of PI controller confirms that the use of a single approach does not necessarily produce optimal results. In this paper, we propose to optimize the performance of the parametres controller by combining two scalable algorithms, genetic algorithms GA and particle Swarm PS, in order to optimize the parameters of the PI controller and to minimize the. By refining the parameters of controleur that monitor performance. Using a search engine that compares the error values of the different approaches and scenarios and, in each scenario, selects the results with the minimum error value. This method has been applied to control the speed of the induction machine. The results obtained by simulation show the high performance and robustness of this technique.