Neural Network Based Optimal Switching Pattern Generation for Multiple Pulse Width Modulated Inverter

A novel concept of application of neural networks for generation of optimal switching patterns in voltage- controlled inverter is presented. In multiple pulse width modulated inverter (PWM) proper selection notch angles can eliminate the specific harmonics. In this work 8 notches per half cycle is assumed. This gives a choice of seven switching angles in a quarter cycle. It is proposed to eliminate all possible lower order harmonics by proper selection of switching angles for different modulation index. A neural network is trained to generate the switching angles and patterns for different modulation index. Simulation results confirm that neural network based switching pattern generation can eliminate all lower order harmonics up to the order 22 nd . The switching patterns for different modulation index, training of neural network and the simulated performance of the inverter are presented.