Implementación de un algoritmo bioinspirado para la sintonización de controladores PID en un rectificador PFC BOOST en medio puente.

Abstract

This document shows the tuning of parameters in a PID controller and a precompensating filter in a PFC Halft Bridge Boost rectifier. An investigation is made to determine a Bioinspired algorithm that can fulfill the optimization that is needed in this project. The clonal selection algorithm based on the natural immune system is chosen and the implementation is carried out in MATLAB/SIMULINK. The constants of the PID controller and the filter are represented by the antigen populations of the algorithm. For tuning, an initial population of 200 antigens is chosen, which is maintained in all iterations, and a memory population of 20 antibodies. At the end of the iterations, this memory population represents the set of tuning solutions, with several local optima and a global optimum, the initial population is not generated randomly but a limited range from a functional solution at one of the rectifier operating points. The error to be minimized is from the power factor variable, it is used in the fitness function. In the population search, limits are established in which the constants can be moved, because the system can become destabilized. The resulting population of the algorithm manages to reach a power factor of 0.998 with a resistive load of 6.6 kOhm. The constants are checked in a real prototype of the plant and compared with the simulated results. In the prototype, the robustness of the solution is also analyzed by changing the operating point of the converter.