Structure-preserved MOR method for coupled systems via orthogonal polynomials and Arnoldi algorithm

This study focuses on the topic of model order reduction (MOR) for coupled systems with inhomogeneous initial conditions and presents an MOR method by general orthogonal polynomials with Arnoldi algorithm. The main procedure is to use a series of expansion coefficients vectors in the space spanned b...

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Veröffentlicht in:	IET circuits, devices & systems Jg. 13; H. 6; S. 879 - 887
Hauptverfasser:	Qi, Zhen-Zhong, Jiang, Yao-Lin, Xiao, Zhi-Hua
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Stevenage The Institution of Engineering and Technology 01.09.2019 John Wiley & Sons, Inc
Schlagworte:	Algorithms Approximation coupled structure coupled systems expansion coefficients vectors general orthogonal polynomials inhomogeneous initial conditions Initial conditions Linear equations Methods model order reduction Model reduction multiorder Arnoldi algorithm Ordinary differential equations Partial differential equations Polynomials recursive formula reduced order systems Research Article structure-preserved MOR method general orthogonal polynomials recursive formula polynomials model order reduction inhomogeneous initial conditions multiorder Arnoldi algorithm reduced order systems expansion coefficients vectors coupled structure structure-preserved MOR method coupled systems
ISSN:	1751-858X, 1751-8598, 1751-8598
Online-Zugang:	Volltext
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Zusammenfassung:	This study focuses on the topic of model order reduction (MOR) for coupled systems with inhomogeneous initial conditions and presents an MOR method by general orthogonal polynomials with Arnoldi algorithm. The main procedure is to use a series of expansion coefficients vectors in the space spanned by orthogonal polynomials that satisfy a recursive formula to generate a projection based on the multiorder Arnoldi algorithm. The resulting model not only match desired number of expansion coefficients but also has the same coupled structure as the original system. Moreover, the stability is preserved as well. The error bound between the outputs is well-discussed. Finally, numerical results show that the authors’ method can deal well with those systems with inhomogeneous initial conditions in the views of accuracy and computational cost.
Bibliographie:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
ISSN:	1751-858X 1751-8598 1751-8598
DOI:	10.1049/iet-cds.2018.5076