Study of Two Control Strategies Based in Fuzzy Logic and Artificial Neural Network Compared with an Optimal Control Strategy Applied to a Buck Converter

Abstract

The dc-dc converters are highly efficient tools used to supply power to different systems, they have a nonlinear behavior and variations at their main parameters could affect their stability. This document studies and compares different control strategies, linear and non linear controllers applied to a Buck converter. There are mainly three control strategies treated in this paper. First an optimal control based design, by employing The quadratic performance index (QPI) is used, second a knowledge based fuzzy control is studied and third an artificial neural network (ANN) as a dynamic emulator of the fuzzy control is proposed. Some comparisons about the systems composed by the plant and a controller, in variation of a few plant parameters were made; in addition the computational time in simulation is compared between the two intelligent controllers.