Resumo

BARRERA, Rene Alexander; PEREZ LONDONO, Sandra Milena  e  MORA FLOREZ, Juan José. Artificial neural networks applied to synchronous machine modeling: a review. Tecnura [online]. 2010, vol.14, n.27, pp.109-122. ISSN 0123-921X.

This paper is devoted to present a bibliographic review of the application of soft computing techniques or artificial intelligence strategies in synchronous machine modeling and parameter identification. Specifically, this paper is emphasized to the application of the artificial neural networks (ANN), due to the common use and their high capability to establish a correlation between the input and output sets in non linear systems. According to the presented review, the ANN has been applied in parameter identification, control systems, transient and steady state stability analysis. As a complement, at the last part of the paper there is a brief description of other commonly used methodologies successfully applied in synchronous machine modeling and parameter identification.

Palavras-chave : Parameter identification; Synchronous machine; Soft computing; Artificial neural networks.

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