Neural-Network-Based Waveform Processing and Delayless Filtering in Power Electronics and AC Drives

This paper systematically explores the static nonlinear mapping property of feedforward neural networks for various waveform processing and delayless filtering that are applicable to power electronics and ac drives area. Neural-network-based processing of waves gives considerable simplification of hardware and/or software that are traditionally used for such applications. Two general cases have been investigated: The voltage or current waveforms which have constant frequency but variable magnitudes, and the other case is variable-frequency variable-magnitude voltage or current waves. The former case is mainly important for power electronics that operate on a utility system and general-purpose constant-frequency converter power supplies, and the latter is important for the adjustable-speed ac drives area. In both cases, the performance of neural-network-based waveform processing and delayless filtering with offline training was found to be excellent. The results of this study are also applicable to other areas of electrical engineering.