Three Frequency-limited Balanced Truncation Algorithms: A Comparison and Three Families of Extensions

Umair Zulfiqar; Xin Du; Qiuyan Song; Victor Sreeram

doi:10.23919/ASCC56756.2022.9828217

Three Frequency-limited Balanced Truncation Algorithms: A Comparison and Three Families of Extensions

Umair Zulfiqar, Xin Du, Qiuyan Song, Victor Sreeram

Electrical, Electronic and Computer Engineering

Research output: Chapter in Book/Conference paper › Conference paper › peer-review

3 Citations (Scopus)

Abstract

In frequency-limited model order reduction, a lower-order approximate model of the high-order model is sought such that it closely approximates the original system within the specified frequency interval. In this paper, three frequency-limited balanced truncation algorithms are qualitatively and quantitatively compared. The pros and cons of each algorithm are discussed. Further, it is noted that these three algorithms can be effortlessly generalized to obtain three families of frequency-limited model order reduction algorithms with interesting properties like stability preservation and availability of apriori error bound expression.

Original language	English
Title of host publication	ASCC 2022 - 2022 13th Asian Control Conference, Proceedings
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	1654-1659
Number of pages	6
ISBN (Electronic)	9788993215236
DOIs	https://doi.org/10.23919/ASCC56756.2022.9828217
Publication status	Published - May 2022
Event	13th Asian Control Conference, ASCC 2022 - Jeju, Korea, Republic of Duration: 4 May 2022 → 7 May 2022

Conference

Conference	13th Asian Control Conference, ASCC 2022
Country/Territory	Korea, Republic of
City	Jeju
Period	4/05/22 → 7/05/22

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10.23919/ASCC56756.2022.9828217

Cite this

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title = "Three Frequency-limited Balanced Truncation Algorithms: A Comparison and Three Families of Extensions",

abstract = "In frequency-limited model order reduction, a lower-order approximate model of the high-order model is sought such that it closely approximates the original system within the specified frequency interval. In this paper, three frequency-limited balanced truncation algorithms are qualitatively and quantitatively compared. The pros and cons of each algorithm are discussed. Further, it is noted that these three algorithms can be effortlessly generalized to obtain three families of frequency-limited model order reduction algorithms with interesting properties like stability preservation and availability of apriori error bound expression. ",

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doi = "10.23919/ASCC56756.2022.9828217",

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Zulfiqar, U, Du, X, Song, Q & Sreeram, V 2022, Three Frequency-limited Balanced Truncation Algorithms: A Comparison and Three Families of Extensions. in ASCC 2022 - 2022 13th Asian Control Conference, Proceedings. IEEE, Institute of Electrical and Electronics Engineers, pp. 1654-1659, 13th Asian Control Conference, ASCC 2022, Jeju, Korea, Republic of, 4/05/22. https://doi.org/10.23919/ASCC56756.2022.9828217

Three Frequency-limited Balanced Truncation Algorithms: A Comparison and Three Families of Extensions. / Zulfiqar, Umair; Du, Xin; Song, Qiuyan et al.
ASCC 2022 - 2022 13th Asian Control Conference, Proceedings. IEEE, Institute of Electrical and Electronics Engineers, 2022. p. 1654-1659.

Research output: Chapter in Book/Conference paper › Conference paper › peer-review

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T1 - Three Frequency-limited Balanced Truncation Algorithms

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AU - Zulfiqar, Umair

AU - Du, Xin

AU - Song, Qiuyan

AU - Sreeram, Victor

PY - 2022/5

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N2 - In frequency-limited model order reduction, a lower-order approximate model of the high-order model is sought such that it closely approximates the original system within the specified frequency interval. In this paper, three frequency-limited balanced truncation algorithms are qualitatively and quantitatively compared. The pros and cons of each algorithm are discussed. Further, it is noted that these three algorithms can be effortlessly generalized to obtain three families of frequency-limited model order reduction algorithms with interesting properties like stability preservation and availability of apriori error bound expression.

AB - In frequency-limited model order reduction, a lower-order approximate model of the high-order model is sought such that it closely approximates the original system within the specified frequency interval. In this paper, three frequency-limited balanced truncation algorithms are qualitatively and quantitatively compared. The pros and cons of each algorithm are discussed. Further, it is noted that these three algorithms can be effortlessly generalized to obtain three families of frequency-limited model order reduction algorithms with interesting properties like stability preservation and availability of apriori error bound expression.

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BT - ASCC 2022 - 2022 13th Asian Control Conference, Proceedings

PB - IEEE, Institute of Electrical and Electronics Engineers

Y2 - 4 May 2022 through 7 May 2022

ER -

Three Frequency-limited Balanced Truncation Algorithms: A Comparison and Three Families of Extensions

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