Stability-Preserving Model Reduction of Networked Lur'e Systems

Yangming Dou*, Xiaodong Cheng*, Jacquelien M.A. Scherpen*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference paperAcademicpeer-review

Abstract

This paper proposes a model reduction approach for simplifying the interconnection topology of Lur'e network systems. A class of reduced-order models are generated by the projection framework based on graph clustering, which not only preserve the network structure but also ensure absolute stability. Furthermore, we provide an upper bound on the input- output approximation error between the original and reduced- order Lur'e network systems, which is expressed as a function of the characteristic matrix of graph clustering. Finally, the results are illustrated via a numerical example.

Original languageEnglish
Title of host publication2024 European Control Conference, ECC 2024
PublisherIEEE
Pages2059-2064
Number of pages6
ISBN (Electronic)9783907144107
DOIs
Publication statusPublished - 2024
Event2024 European Control Conference, ECC 2024 - Stockholm, Sweden
Duration: 25 Jun 202428 Jun 2024

Conference

Conference2024 European Control Conference, ECC 2024
Country/TerritorySweden
CityStockholm
Period25/06/2428/06/24

Keywords

  • absolute stability
  • graph clustering
  • Lur'e system
  • model reduction

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