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IJSEA Archive (Volume 6, Issue 10)

International Journal of Science and Engineering Applications (IJSEA)  (Volume 6, Issue 10 October 2017)

Prediction of Excitation Angles for a Switched Reluctance Generator using Artificial Neural Network

Pairote Thongprasri


Keywords: artificial neural network; feed-forward; back-propagation; hidden layer; output layer

Abstract References BibText

        This paper presents a method to determine excitation angles for a Switched Reluctance Generator (SRG) by using Artificial Neural Network (ANN). The ANN model consists of the feed-forward neural network and the back-propagation learning with a linear activation function (the linear function) and a nonlinear function (the hyperbolic tangent). The ANN model with two layers; the hidden layer and the output layer, is derived from the current and flux linkage of the SRG. The SRG model is built from the magnetization curve which the flux linkage versus current at different rotor positions is analyzed from the finite element method (FEM). An 8/6 SRG was set up to validate the proposed ANN method.

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title = " Curriculum Delivery Constraints of Arabic Language as a Foreign Language in the UAE ",
journal = "International Journal of Science and Engineering Applications (IJSEA)",
volume = "6",
number = "9",
pages = "296 - 301 ",
year = "2017",
author = " Pairote Thongprasri ",