Optimal H∞ LMI-Based Model Reduction by Moment Matching for Linear Time-Invariant Models

M.F. (Fahim) Shakib; Giordano Scarciotti; M. Jungers; A.Y. Pogromskiy; Alexei Pavlov; N. van de Wouw

doi:10.1109/CDC45484.2021.9683148

Optimal H∞ LMI-Based Model Reduction by Moment Matching for Linear Time-Invariant Models

M.F. (Fahim) Shakib, Giordano Scarciotti, M. Jungers, A.Y. Pogromskiy, Alexei Pavlov, N. van de Wouw

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

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This paper proposes an approach to model order reduction of stable linear time-invariant (LTI) models. The proposed approach extends time-domain moment matching by the minimization of the H_infty norm of the error dynamics characterizing the difference between the full-order and reduced-order models given fixed interpolation points. The optimal H_infty moment matching problem is a constrained optimization problem with bilinear constraints. Introducing a novel numerical procedure, we minimize the approximation error, while respecting the constraints and, thereby, find a suboptimal H_infty reduced-order model. The effectiveness of the approach is
illustrated in a numerical example.

Originele taal-2	Engels
Titel	60th IEEE Conference on Decision and Control (CDC 2021)
Uitgeverij	Institute of Electrical and Electronics Engineers
Pagina's	6914-6919
Aantal pagina's	6
ISBN van elektronische versie	978-1-6654-3659-5
DOI's	https://doi.org/10.1109/CDC45484.2021.9683148
Status	Gepubliceerd - 1 feb. 2022
Evenement	2021 60th IEEE Conference on Decision and Control (CDC) - Austin, TX, USA, Austin, Verenigde Staten van Amerika Duur: 13 dec. 2021 → 17 dec. 2021 Congresnummer: 60 https://2021.ieeecdc.org/

Congres

Congres	2021 60th IEEE Conference on Decision and Control (CDC)
Verkorte titel	CDC 2021
Land/Regio	Verenigde Staten van Amerika
Stad	Austin
Periode	13/12/21 → 17/12/21
Internet adres	https://2021.ieeecdc.org/

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10.1109/CDC45484.2021.9683148

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Shakib, M. F., Scarciotti, G., Jungers, M., Pogromskiy, A. Y., Pavlov, A., & van de Wouw, N. (2022). Optimal H∞ LMI-Based Model Reduction by Moment Matching for Linear Time-Invariant Models. In 60th IEEE Conference on Decision and Control (CDC 2021) (blz. 6914-6919). Artikel 9683148 Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/CDC45484.2021.9683148

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title = "Optimal H∞ LMI-Based Model Reduction by Moment Matching for Linear Time-Invariant Models",

abstract = "This paper proposes an approach to model order reduction of stable linear time-invariant (LTI) models. The proposed approach extends time-domain moment matching by the minimization of the H∞ norm of the error dynamics characterizing the difference between the full-order and reduced-order models given fixed interpolation points. The optimal H∞ moment matching problem is a constrained optimization problem with bilinear constraints. Introducing a novel numerical procedure, we minimize the approximation error, while respecting the constraints and, thereby, find a suboptimal H∞ reduced-order model. The effectiveness of the approach is illustrated in a numerical example.",

author = "Shakib, {M.F. (Fahim)} and Giordano Scarciotti and M. Jungers and A.Y. Pogromskiy and Alexei Pavlov and {van de Wouw}, N.",

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doi = "10.1109/CDC45484.2021.9683148",

language = "English",

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booktitle = "60th IEEE Conference on Decision and Control (CDC 2021)",

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note = "60th IEEE Conference on Decision and Control, CDC 2021, CDC 2021 ; Conference date: 13-12-2021 Through 17-12-2021",

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Shakib, MF, Scarciotti, G, Jungers, M, Pogromskiy, AY, Pavlov, A & van de Wouw, N 2022, Optimal H∞ LMI-Based Model Reduction by Moment Matching for Linear Time-Invariant Models. in 60th IEEE Conference on Decision and Control (CDC 2021)., 9683148, Institute of Electrical and Electronics Engineers, blz. 6914-6919, 2021 60th IEEE Conference on Decision and Control (CDC), Austin, Texas, Verenigde Staten van Amerika, 13/12/21. https://doi.org/10.1109/CDC45484.2021.9683148

Optimal H∞ LMI-Based Model Reduction by Moment Matching for Linear Time-Invariant Models. / Shakib, M.F. (Fahim); Scarciotti, Giordano; Jungers, M. et al.
60th IEEE Conference on Decision and Control (CDC 2021). Institute of Electrical and Electronics Engineers, 2022. blz. 6914-6919 9683148.

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

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AU - Shakib, M.F. (Fahim)

AU - Scarciotti, Giordano

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AU - Pavlov, Alexei

AU - van de Wouw, N.

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N2 - This paper proposes an approach to model order reduction of stable linear time-invariant (LTI) models. The proposed approach extends time-domain moment matching by the minimization of the H∞ norm of the error dynamics characterizing the difference between the full-order and reduced-order models given fixed interpolation points. The optimal H∞ moment matching problem is a constrained optimization problem with bilinear constraints. Introducing a novel numerical procedure, we minimize the approximation error, while respecting the constraints and, thereby, find a suboptimal H∞ reduced-order model. The effectiveness of the approach is illustrated in a numerical example.

AB - This paper proposes an approach to model order reduction of stable linear time-invariant (LTI) models. The proposed approach extends time-domain moment matching by the minimization of the H∞ norm of the error dynamics characterizing the difference between the full-order and reduced-order models given fixed interpolation points. The optimal H∞ moment matching problem is a constrained optimization problem with bilinear constraints. Introducing a novel numerical procedure, we minimize the approximation error, while respecting the constraints and, thereby, find a suboptimal H∞ reduced-order model. The effectiveness of the approach is illustrated in a numerical example.

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ER -

Optimal H∞ LMI-Based Model Reduction by Moment Matching for Linear Time-Invariant Models

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