Computational techniques for H2 optimal frequency-limited model order reduction of large-scale sparse linear systems

Autor:	A. Mostakim Fony, Kife I. Bin Iqbal, Mohammad-Sahadet Hossain, Mian Ilyas Ahmad, Xin Du, Md. Tanzim Hossain, M. Monir Uddin
Rok vydání:	2021
Předmět:	Set (abstract data type) Model order reduction Matrix (mathematics) General Computer Science Scale (ratio) Computer science Modeling and Simulation Descriptor systems Linear system Algorithm Theoretical Computer Science
Zdroj:	Journal of Computational Science. 55:101473
ISSN:	1877-7503
DOI:	10.1016/j.jocs.2021.101473
Popis:	We consider the problem of frequency limited H 2 optimal model order reduction for large-scale sparse linear systems. A set of first-order H 2 optimality conditions are derived for the frequency limited model order reduction problem. These conditions involve the solution of two frequency limited Sylvester equations that are known to be computationally complex. We discuss a framework for solving these matrix equations efficiently. The idea is also extended to the frequency limited H 2 optimal model order reduction of index-1 descriptor systems. Numerical experiments are carried out using Python programming language and the results are presented to demonstrate the approximation accuracy and computational efficiency of the proposed technique.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::0e4eb54e4a9b22c0f65da50f68516220 https://doi.org/10.1016/j.jocs.2021.101473 Zobrazit plný text záznamu Full Text from ScienceDirect