MATEC Web Conf.
Volume 329, 2020International Conference on Modern Trends in Manufacturing Technologies and Equipment: Mechanical Engineering and Materials Science (ICMTMTE 2020)
|Number of page(s)||5|
|Published online||26 November 2020|
Neural network identification of a nonlinear model of a high-pressure sodium lamp
1 Department of Information Measuring Equipment and Metrology, Penza State University, Penza, Russia
2 Department of Information Security and Service, National Research Mordovia State University, Saransk, Russia
* Corresponding author: firstname.lastname@example.org
The article is devoted to the identification of a high-pressure sodium lamp nonlinear model parameters based on neural network technologies. Identification was carried out using a dynamic neural network. The model had 17 parameters based on second order differential equations. As a result, out of 17 parameters, four were selected that accurately reflect the real picture of the model.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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