Backpropagation Neural Network Adaptive Voltage Control of a High-Gain Transformerless DC/DC Boost Converter for solar applications

Abstract

An artificial neural network (ANN) adaptive control method for high-gain transformerless DC-DC boost converter is designed in order to achieve better performance and robustness. An ANN controller have the ability to predict the duty cycle in each moment because it is already trained  with a vast number of random values of input, output and reference voltages. In order to minimize the error of obtaining the most convenient duty cycle, a back-propagation algorithm has been used to train the neural network because it has the ability to deal with the weights constantly for the sake of diminishing the loss function which makes the ANN generates the fittest duty cycle. The control scheme has been done for a photovoltaic system and the simulation is done using Matlab/Simulink. Simulation results are given for irradiance, reference voltage and load variations. The results are designated to prove the effectiveness of the proposed control system.