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
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ISSN:1751-858X, 1751-8598, 1751-8598
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Abstract 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.
AbstractList 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.
Author Jiang, Yao-Lin
Xiao, Zhi-Hua
Qi, Zhen-Zhong
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  givenname: Yao-Lin
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  givenname: Zhi-Hua
  surname: Xiao
  fullname: Xiao, Zhi-Hua
  organization: 3School of Information and Mathematics, Yangtze University, Jingzhou, Hubei 434023, People's Republic of China
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crossref_primary_10_1093_imamci_dnad034
crossref_primary_10_1093_imamci_dnae018
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Issue 6
Keywords 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
Language English
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Snippet 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...
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SubjectTerms 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
Title Structure-preserved MOR method for coupled systems via orthogonal polynomials and Arnoldi algorithm
URI http://digital-library.theiet.org/content/journals/10.1049/iet-cds.2018.5076
https://onlinelibrary.wiley.com/doi/abs/10.1049%2Fiet-cds.2018.5076
https://www.proquest.com/docview/3092276344
Volume 13
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