A single-layer neural network-based voltage compensation technique which generates minimum-distortion sinusoidal output voltages from a three-phase PWM inverter used for uninterruptible power supplies (UPS) is described. The proposed compensation technique is implemented in a microprocessor-based controller constructed in the stationary d-q frame where the controller sampling rate is twice the inverter switching frequency. The structure of a feed-forward artificial neural network connects network inputs and outputs through multiple linear or nonlinear neuron models, and processes these input/output data associations in a parallel distributed manner. Network inputs in the form of UPS load voltage commands and load current feedback are propagated forward in the network each controller sampling period generating the inverter output voltage commands, the network outputs, which are converted to three phase inverter switching Signals using the space vector PWM waveform generation process. / Ph. D.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/39997 |
| Date | 19 October 2006 |
| Creators | Barnes, Lemuel Gregory III |
| Contributors | Electrical Engineering, Ramu, Krishnan, Nunnally, Charles E., VanLandingham, Hugh F., Chen, Dan Y., Deisenroth, Michael P. |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Dissertation, Text |
| Format | xxi, 393 leaves, BTD, application/pdf, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
| Relation | OCLC# 30986141, LD5655.V856_1994.B376.pdf |
Page generated in 0.0022 seconds