Title :
A Simplified Three-Dimensional Space Vector Algorithm for Three-phase Four-leg Converters Based on Classifier Neural Networks
Author :
Baghernejad, R. ; Bakhshai, A. ; Yazdani, D.
Author_Institution :
Dept. of ECE, Isfahan Univ. of Technol.
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 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 avoids non-linear function approximations, and removes any dependency on complicated look-up tables. This advantage makes the use of the proposed technique of major gains in modern power systems and applications such as packaging technology and application-specific integrated circuit (ASIC) design. The proposed scheme is validated by analytical analysis, and simulations on a four-leg voltage-source converter
Keywords :
application specific integrated circuits; approximation theory; neural nets; nonlinear functions; power convertors; power engineering computing; table lookup; ASIC design; application-specific integrated circuit; classifier neural networks; lookup tables; neurocomputing classification algorithm; nonlinear function approximations; packaging technology; space vector modulation; three-dimensional space vector algorithm; three-phase four-leg voltage source converters; zero-sequence current; Application specific integrated circuits; Classification algorithms; Computational intelligence; Inverters; Neural networks; Power system simulation; Space technology; Support vector machine classification; Support vector machines; Voltage;
Conference_Titel :
Power Electronics Specialists Conference, 2005. PESC '05. IEEE 36th
Conference_Location :
Recife
Print_ISBN :
0-7803-9033-4
DOI :
10.1109/PESC.2005.1581742