Model Reduction by Moment Matching for Convergent Lur'e-Type Models

M.F. Shakib; G. Scarciotti; A.Y. Pogromsky; A. Pavlov; N. van de Wouw

doi:10.23919/ACC50511.2021.9482908

Model Reduction by Moment Matching for Convergent Lur'e-Type Models

M.F. Shakib, G. Scarciotti, A.Y. Pogromsky, A. Pavlov, N. van de Wouw

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

4 Citations (Scopus)

Abstract

This paper proposes an approach to model order reduction of convergent Lur'e-type models, which consist of a linear time-invariant (LTI) block and a static nonlinear block that is placed in feedback with the LTI block. In the proposed approach, we match a finite number of moments of the LTI block and keep the static nonlinear block to approximate the moments of the Lur'e-type model. The benefits of this approach are that the Lur'e-type structure is preserved after reduction, that the reduction method has an interpretation in terms of the frequency response function of the LTI block and that global exponential stability properties of the full-order model are preserved. The effectiveness of the approach is illustrated in a numerical example.

Original language	English
Title of host publication	2021 American Control Conference (ACC)
Publisher	Institute of Electrical and Electronics Engineers
Pages	4459-4464
Number of pages	6
ISBN (Electronic)	9781665441971
DOIs	https://doi.org/10.23919/ACC50511.2021.9482908
Publication status	Published - 28 Jul 2021
Event	2021 American Control Conference, ACC 2021 - Virtual, Virtual, New Orleans, United States Duration: 25 May 2021 → 28 May 2021 http://acc2021.a2c2.org/

Conference

Conference	2021 American Control Conference, ACC 2021
Abbreviated title	ACC 2021
Country/Territory	United States
City	Virtual, New Orleans
Period	25/05/21 → 28/05/21
Internet address	http://acc2021.a2c2.org/

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10.23919/ACC50511.2021.9482908

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title = "Model Reduction by Moment Matching for Convergent Lur'e-Type Models",

abstract = "This paper proposes an approach to model order reduction of convergent Lur'e-type models, which consist of a linear time-invariant (LTI) block and a static nonlinear block that is placed in feedback with the LTI block. In the proposed approach, we match a finite number of moments of the LTI block and keep the static nonlinear block to approximate the moments of the Lur'e-type model. The benefits of this approach are that the Lur'e-type structure is preserved after reduction, that the reduction method has an interpretation in terms of the frequency response function of the LTI block and that global exponential stability properties of the full-order model are preserved. The effectiveness of the approach is illustrated in a numerical example.",

author = "M.F. Shakib and G. Scarciotti and A.Y. Pogromsky and A. Pavlov and {van de Wouw}, N.",

note = "Publisher Copyright: {\textcopyright} 2021 American Automatic Control Council.; 2021 American Control Conference, ACC 2021, ACC 2021 ; Conference date: 25-05-2021 Through 28-05-2021",

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doi = "10.23919/ACC50511.2021.9482908",

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Shakib, MF, Scarciotti, G, Pogromsky, AY, Pavlov, A & van de Wouw, N 2021, Model Reduction by Moment Matching for Convergent Lur'e-Type Models. in 2021 American Control Conference (ACC)., 9482908, Institute of Electrical and Electronics Engineers, pp. 4459-4464, 2021 American Control Conference, ACC 2021, Virtual, New Orleans, United States, 25/05/21. https://doi.org/10.23919/ACC50511.2021.9482908

TY - GEN

T1 - Model Reduction by Moment Matching for Convergent Lur'e-Type Models

AU - Shakib, M.F.

AU - Scarciotti, G.

AU - Pogromsky, A.Y.

AU - Pavlov, A.

AU - van de Wouw, N.

PY - 2021/7/28

Y1 - 2021/7/28

N2 - This paper proposes an approach to model order reduction of convergent Lur'e-type models, which consist of a linear time-invariant (LTI) block and a static nonlinear block that is placed in feedback with the LTI block. In the proposed approach, we match a finite number of moments of the LTI block and keep the static nonlinear block to approximate the moments of the Lur'e-type model. The benefits of this approach are that the Lur'e-type structure is preserved after reduction, that the reduction method has an interpretation in terms of the frequency response function of the LTI block and that global exponential stability properties of the full-order model are preserved. The effectiveness of the approach is illustrated in a numerical example.

AB - This paper proposes an approach to model order reduction of convergent Lur'e-type models, which consist of a linear time-invariant (LTI) block and a static nonlinear block that is placed in feedback with the LTI block. In the proposed approach, we match a finite number of moments of the LTI block and keep the static nonlinear block to approximate the moments of the Lur'e-type model. The benefits of this approach are that the Lur'e-type structure is preserved after reduction, that the reduction method has an interpretation in terms of the frequency response function of the LTI block and that global exponential stability properties of the full-order model are preserved. The effectiveness of the approach is illustrated in a numerical example.

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U2 - 10.23919/ACC50511.2021.9482908

DO - 10.23919/ACC50511.2021.9482908

M3 - Conference contribution

AN - SCOPUS:85111922740

SP - 4459

EP - 4464

BT - 2021 American Control Conference (ACC)

PB - Institute of Electrical and Electronics Engineers

T2 - 2021 American Control Conference, ACC 2021

Y2 - 25 May 2021 through 28 May 2021

ER -

Model Reduction by Moment Matching for Convergent Lur'e-Type Models

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