Controle neural aplicado a um conversor boost utilizado em aerogeradores de baixa potência

Abstract

This work presents the study, design and simulation of a DC boost converter with output voltage control using neural networks. The boost converter studied in this work is being used in a wind turbine low power, with maximum power of 3kW. Due to the operation of the variable speed of the wind turbine, the input voltage of the converter is also variable over a wide operating range, and the output must be stabilized to a fixed voltage. This means that there is a need to control the converter so that differences in input voltage are compensated. To compensation this difference, a controller was designed using the root locus method. The modeling of the boost converter is also presented. The controller provides the time of operation of power semiconductor switch used in the converter, thereby controlling the output voltage. The variation in input voltage, which can vary from 50V to 350V, makes the driver does not act optimally for all operating points. Thus, a neural controller is designed to work as a controller, compensating disturbances of the converter input voltage. The validation of this controller was performed by simulation using Matlab / Simulink software, to confirm the theoretical development presented in the work.