MATEC Web Conf.
Volume 226, 2018XIV International Scientific-Technical Conference “Dynamic of Technical Systems” (DTS-2018)
|Number of page(s)||10|
|Section||4 Fundamental methods of system analysis, modeling and optimization of dynamic systems|
|Published online||07 November 2018|
Study of methods for dimension reduction of complex dynamic linear systems models
1 Platov South-Russian State Polytechnic University (NPI), Information Measuring Systems and Technologies Department, 346428 Novocherkassk, Russia
2 TU Dortmund, Department of Electrical Engineering and Information Technology, 44227 Dortmund, Germany
* Corresponding author: firstname.lastname@example.org
Complex dynamic linear systems of equations are solved by numerical iterative methods, which need much computation and are timeconsuming ones, and the optimization stage requires repeated solution of these equation systems that increases the time on development. To shorten the computation time, various methods can be applied, among them preliminary (estimated) calculation or oversimple models calculation, however, while testing and optimizing the full model is used. Reduced order models are very popular in solving this problem. The main idea of a reduced order model is to find a simplified model that may reflect the required properties of the original model as accurately as possible. There are many methods for the model order reduction, which have their advantages and disadvantages. In this article, a method based on Krylov subspaces and SVD methods is considered. A numerical experiments is given.
© The Authors, published by EDP Sciences, 2018
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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