Diseño y simulación de un control neuronal aplicado a un convertidor flyback para la regulación de tensión

Abstract

This article explains the design and simulation of a controller based on neural networks to regulate the output voltage of a flyback converter. Neural networks are used since they do not require a mathematical model of the converter, with the advantage of a greater operating range than traditional control methods. In the training process, changes were made in the database and in the neural network architecture to get a more appropriate controller that the guaranteed line and load regulation of the converter. The functional neural controller validation was made on Simulink with the circuital model of a flyback converter, putting it to changes of output load and input voltage. The results obtained show the effectiveness of neuronal control with its ability to regulate lines in a range of 20V to 50V, load regulation between 8Ω and 12Ω, and whose architecture is made up of four neurons.