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|Title:||Design and implementation of a neural-network-controlled UPS inverter|
Two term control systems
Uninterruptible power systems
|Source:||IECON'99 proceedings : the 25th annual conference of the IEEE Industrial Electronics Society : November 29-December 3, 1999, San Jose, California, USA, p. 779-784 How to cite?|
|Abstract:||A low-cost analog neural network control scheme for the inverters of Uninterruptible Power Supplies (UPS) is proposed to achieve low total harmonics distortion (THD) output voltage and good dynamic response. Such a scheme is based on learning control law from representative example patterns obtained from two simulation models. One is a multiple-feedback-loop controller for linear loads, and the other is a novel idealized load-current-feedback controller specially designed for nonlinear loads. Example patterns for various loading conditions are used in the off-line training of a selected neural network. When the training is completed, the neural network is used to control the UPS inverter on-line. A simple analog hardware is built to implement the proposed neural network controller, an optimized PI controller is built as well. Experimental results show that the proposed neural-network-controlled inverter achieves lower THD and better dynamic responses than the PI-controlled inverter does.|
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|Appears in Collections:||Conference Paper|
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