Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/1446
Title: Analogue implementation of a neural network controller for UPS inverter applications
Authors: Sun, X
Chow, MHL 
Leung, FHF 
Xu, D
Wang, Y
Lee, YS
Keywords: Neural network control
UPS inverter
Issue Date: May-2002
Publisher: IEEE
Source: IEEE transactions on power electronics, May 2002, v. 17, no. 3, p. 305-313 How to cite?
Journal: IEEE transactions on power electronics 
Abstract: An analogue neural-network controller for UPS inverter applications is presented. The proposed neural-network controller is trained off-line using patterns obtained from a simulated controller, which had an idealized load-current-reference. Simulation results show that the proposed neural-network controller can achieve low total harmonic distortion under nonlinear loading condition and good dynamic responses under transient loading condition. To verify the performance of the proposed NN controller, a hardware inverter with an analogue neural network (NN) controller (using mainly operational amplifiers and resistors) is built. Additionally, for comparison purposes, a PI controller with optimized parameters is built. Experimental results confirm the simulation results and show the superior performance of the NN controller especially under rectifier-type loading condition. Implementing the analogue neural-network controller using programmable integrated circuits is also discussed.
URI: http://hdl.handle.net/10397/1446
ISSN: 0885-8993
DOI: 10.1109/TPEL.2002.1004238
Rights: © 2002 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
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