A comparative performance assessment of conventional and ANN based SVPWM controller for VFI induction motor drive

In this paper, space vector pulse width modulation (SVPWM) scheme for voltage fed inverter (VFI) using conventional method and artificial neural network (ANN) based approach are presented separately. In the conventional method, the difficulty of explicitly expressing cross-over and holding-angle as a function of modulation factor in overmodulation mode-I and mode-II respectively are overcome by introducing Newton's Forward Interpolation (NFI). This greatly simplifies the implementation of conventional SVPWM technique without compromising the accuracy issue. The SVPWM is further implemented by ANN based approach built with three subnets to account for three regions of inverter operation distinctly. In comparison to a single ANN taking care of all the three regions, this apparent redundancy of subnets markedly reduces the error in calculating turn-on time for inverter switches. The performances of these two schemes are quantitatively expressed by total harmonic distortion in motor phase current by simulation in Matlab. The results show that ANN based approach shows a comparable performance with that of the conventional approach.