ℋ2 sub-optimal model reduction for second-order network systems

Lanlin Yu; Xiaodong Cheng; Jacquelien M.A. Scherpen; Emma Gort

doi:10.1109/CDC40024.2019.9029735

ℋ2 sub-optimal model reduction for second-order network systems

Lanlin Yu, Xiaodong Cheng, Jacquelien M.A. Scherpen, Emma Gort

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

Abstract

This paper studies a moment matching model reduction method for second-order network systems. For a given complex second-order network system, our goal is to find a reduced second-order network system that achieves moment matching. Firstly, the original second-order network system is split into an asymptotically stable subsystem and an average subsystem. Then, moment matching approach is implemented to reduce the dimension of the asymptotically stable subsystem. The resulting reduced-order model is combined with the average subsystem, leading to a reduced second-order system preserves the semistability. Subsequently, a specific coordinate transform allows for the reduced-order model to be converted to a complete network. A mass-spring-damper network demonstrates the effectiveness of the proposed method.

Original language	English
Title of host publication	2019 IEEE 58th Conference on Decision and Control, CDC 2019
Place of Publication	Piscataway
Publisher	Institute of Electrical and Electronics Engineers
Pages	5062-5067
Number of pages	6
ISBN (Electronic)	978-1-7281-1398-2
DOIs	https://doi.org/10.1109/CDC40024.2019.9029735
Publication status	Published - 12 Mar 2020
Event	58th IEEE Conference on Decision and Control (CDC 2019) - Nice, France Duration: 11 Dec 2019 → 13 Dec 2019 https://cdc2019.ieeecss.org/

Conference

Conference	58th IEEE Conference on Decision and Control (CDC 2019)
Abbreviated title	CDC 2019
Country	France
City	Nice
Period	11/12/19 → 13/12/19
Internet address	https://cdc2019.ieeecss.org/

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title = "ℋ2 sub-optimal model reduction for second-order network systems",

abstract = "This paper studies a moment matching model reduction method for second-order network systems. For a given complex second-order network system, our goal is to find a reduced second-order network system that achieves moment matching. Firstly, the original second-order network system is split into an asymptotically stable subsystem and an average subsystem. Then, moment matching approach is implemented to reduce the dimension of the asymptotically stable subsystem. The resulting reduced-order model is combined with the average subsystem, leading to a reduced second-order system preserves the semistability. Subsequently, a specific coordinate transform allows for the reduced-order model to be converted to a complete network. A mass-spring-damper network demonstrates the effectiveness of the proposed method.",

author = "Lanlin Yu and Xiaodong Cheng and Scherpen, {Jacquelien M.A.} and Emma Gort",

year = "2020",

month = mar,

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doi = "10.1109/CDC40024.2019.9029735",

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booktitle = "2019 IEEE 58th Conference on Decision and Control, CDC 2019",

publisher = "Institute of Electrical and Electronics Engineers",

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note = "58th IEEE Conference on Decision and Control (CDC 2019), CDC 2019 ; Conference date: 11-12-2019 Through 13-12-2019",

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Yu, L, Cheng, X, Scherpen, JMA & Gort, E 2020, ℋ2 sub-optimal model reduction for second-order network systems. in 2019 IEEE 58th Conference on Decision and Control, CDC 2019., 9029735, Institute of Electrical and Electronics Engineers, Piscataway, pp. 5062-5067, 58th IEEE Conference on Decision and Control (CDC 2019), Nice, France, 11/12/19. https://doi.org/10.1109/CDC40024.2019.9029735

ℋ2 sub-optimal model reduction for second-order network systems. / Yu, Lanlin; Cheng, Xiaodong; Scherpen, Jacquelien M.A.; Gort, Emma.

2019 IEEE 58th Conference on Decision and Control, CDC 2019. Piscataway : Institute of Electrical and Electronics Engineers, 2020. p. 5062-5067 9029735.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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N2 - This paper studies a moment matching model reduction method for second-order network systems. For a given complex second-order network system, our goal is to find a reduced second-order network system that achieves moment matching. Firstly, the original second-order network system is split into an asymptotically stable subsystem and an average subsystem. Then, moment matching approach is implemented to reduce the dimension of the asymptotically stable subsystem. The resulting reduced-order model is combined with the average subsystem, leading to a reduced second-order system preserves the semistability. Subsequently, a specific coordinate transform allows for the reduced-order model to be converted to a complete network. A mass-spring-damper network demonstrates the effectiveness of the proposed method.

AB - This paper studies a moment matching model reduction method for second-order network systems. For a given complex second-order network system, our goal is to find a reduced second-order network system that achieves moment matching. Firstly, the original second-order network system is split into an asymptotically stable subsystem and an average subsystem. Then, moment matching approach is implemented to reduce the dimension of the asymptotically stable subsystem. The resulting reduced-order model is combined with the average subsystem, leading to a reduced second-order system preserves the semistability. Subsequently, a specific coordinate transform allows for the reduced-order model to be converted to a complete network. A mass-spring-damper network demonstrates the effectiveness of the proposed method.

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BT - 2019 IEEE 58th Conference on Decision and Control, CDC 2019

PB - Institute of Electrical and Electronics Engineers

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T2 - 58th IEEE Conference on Decision and Control (CDC 2019)

Y2 - 11 December 2019 through 13 December 2019

ER -

ℋ2 sub-optimal model reduction for second-order network systems

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