Research of SVPWM Based on ANN in Photovoltaic Grid-Connected Inverter

The basic principle of space voltage vector Pulse Wide Modulation (SVPWM) is analyzed, and a novel algorithm for SVPWM based on Artificial neural network (ANN) is proposed. This ANN SVPWM controller completely covers the under-modulation and over-modulation linearly extending operation smoothly up to the six-step mode. The neural network controller has the advantage of very fast implementation by using SVPWM algorithm, and it can increase the switching frequency of power switches in the static converter. In this design, the individual training strategy with the fixed weight and supervised models have used. The simulation is developed by using MATLAB, together with the Neural Network Toolbox for training the ANN-controller. The simulation results show that the neural network control strategy during over-modulation period features simplicity, high efficiency and excellent control effect.