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   A Neuro-Based Classification Algorithm for Implementation of Space Vector Modulation for Multi-Level Converters   [View] 
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 Author(s)   Maryam Saeedifard, Hamidreza Saligheh Rad, Alireza Bakhshai, Reza Iravani 
 Abstract   
This paper proposes a novel, simple and fast classification algorithm for implementation of Space Vector Modulation (SVM) method for a multi-level Diode Clamped Converter (DCC) with any number of levels. The proposed algorithm is based on a classifier neural network. The proposed algorithm provides a straightforward and computationally efficient approach without the use of trigonometric calculations or look-up tables to identify the location of reference voltage vector, its adjacent switching voltage vectors, and their corresponding on-duration time intervals. The feasibility of the proposed SVM algorithm is validated based on theoretical analysis, simulation studies and experimental tests on a DSP-controlled, 5 kVA, three-level DCC system.
 
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Filename:Unnamed file
Filesize:297.1 KB
 Type   Members Only 
 Date   Last modified 2008-07-24 by System