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Content Provider | IEEE Xplore Digital Library |
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Author | Baghernejad, R. Bakhshai, A. Yazdani, D. |
Copyright Year | 2005 |
Description | Author affiliation: Dept. of Electr. & Comput. Eng., Isafahan Univ. of Technol. (Baghernejad, R.) |
Abstract | Four-leg voltage source converters have successfully been used to nullify the zero-sequence current generated by unbalanced or nonlinear loads. This paper introduces an on-line, simple, intelligent, and computationally efficient neuro-computing classification algorithm for the implementation of three-dimensional space vector modulation (SVM) on four-leg voltage-source inverters. The proposed technique uses the concepts of counter propagation neural networks (CPN) for prism identification, and employs a nonlinear classifier network for tetrahedron identification. Nonlinear function approximations and bulky look up tables are successfully avoided, and exact positioning of the switching instants is obtained. Analytical analysis and simulations on a four-leg voltage-source converter validate the proposed scheme |
File Size | 754830 |
File Format | |
ISBN | 0780392523 |
DOI | 10.1109/IECON.2005.1569052 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2005-11-06 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Voltage Computational intelligence Classification algorithms Support vector machines Support vector machine classification Inverters Counting circuits Neural networks Function approximation Analytical models |
Content Type | Text |
Resource Type | Article |
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