A Neural-Network-Based Space-Vector PWM Controller for Voltage-Fed Inverter Induction Motor Drive

A neural-network-based implementation of space-vector modulation (SVM) of a voltage-fed inverter has been proposed in this paper that fully covers the undermodulation and overmodulation regions linearly extending operation smoothly up to square wave. A neural network has the advantage of very fast implementation of an SVM algorithm that can increase the converter switching frequency, particularly when a dedicated application-specific integrated circuit chip is used in the modulator. The scheme has been fully implemented and extensively evaluated in a V/Hz-controlled 5-hp 60-Hz 230-V induction motor drive. The performances of the drive with artificial-neural-network-based SVM are excellent. The scheme can be easily extended to a vector-controlled drive.