Artificial neural network-based nonlinear black-box modeling of synchronous generators

Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/24761

Title:	Artificial neural network-based nonlinear black-box modeling of synchronous generators
Authors:	Micev, M Ćalasan, M Radulović, M Abdel Aleem, SHE Hasanien, HM Zobaa, AF
Keywords:	artificial neural networks;automatic voltage regulation;experimental measurements;Levenberg-Marquardt algorithm;nonlinear modeling;parameter identification;synchronous generators
Issue Date:	1-Jul-2022
Publisher:	Institute of Electrical and Electronics Engineers (IEEE)
Citation:	Micev, M., Ćalasan, M., Radulović, M., Abdel Aleem, S.H.E., Hasanien, H.M. and Zobaa, A.F. (2022) 'Artificial neural network-based nonlinear black-box modeling of synchronous generators', IEEE Transactions on Industrial Informatics, 0 (in press), pp. 1-12. doi: 10.1109/TII.2022.3187740.
Description:	Data availability: The complete experimental measurements presented in Figs. 6 and 7, along with some of the used Matlab codes and Simulink models, are located on the following link: https://drive.google.com/file/d/1OlNfo56QIgJUaKioGhenOJ28WNt88y3/view?usp=sharing. It can be downloaded with the permission of the authors.
URI:	https://bura.brunel.ac.uk/handle/2438/24761
DOI:	https://doi.org/10.1109/TII.2022.3187740
ISSN:	1551-3203
Appears in Collections:	Dept of Electronic and Electrical Engineering Embargoed Research Papers

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