The development of artificial neural network space vector PWM for four-switch three-phase inverter

Abstract

This paper presents the development of neural network-based controller of space vector modulation (ANN-SVPWM) for low cost voltage source inverters. This ANN-SVPWM controller completely covers the undermodulation and overmodulation modes with operation extended linearly and smoothly up to square wave (six-step). The ANN controller has the advantage of the very fast implementation of an SVM algorithm that can increase the switching frequency of power switches of the static converter, this point has a very important sense for minimizing DC bus capacitance, unbalanced DC source and the ripple of load current. The ANN controller uses the individual training strategy with the fixed weight and supervised models. A computer simulation program is developed using Matlab/Simulink together with the Neural Network Toolbox for training the ANN-controller. © 2007 IEEE.