Publication

Reduction of Second-Order Network Systems with Structure Preservation

Cheng, X., Kawano, Y. & Scherpen, J. M. A., Oct-2017, In : IEEE Transactions on Automatic Control. 62, 10, p. 5026-5038

Research output: Contribution to journalArticleAcademicpeer-review

Copy link to clipboard

Documents

  • XiaodongTAC07874139

    Final author's version, 1 MB, PDF document

  • Reduction of Second-Order Network Systems With Structure Preservation

    Final publisher's version, 2 MB, PDF document

    Request copy

DOI

This paper proposes a general framework for structure-preserving model reduction of a second-order network system based on graph clustering. In this approach, vertex dynamics are captured by the transfer functions from inputs to individual states, and the dissimilarities of vertices are quantified by the H_2-norms of the transfer function discrepancies. A greedy hierarchical clustering algorithm is proposed to place those vertices with similar dynamics into same clusters. Then, the reduced-order model is generated by the Petrov-Galerkin method, where the projection is formed by the characteristic matrix of the resulting network clustering. It is shown that the simplified system preserves an interconnection structure, i.e., it can be again interpreted as a second-order system evolving over a reduced graph. Furthermore, this paper generalizes the definition of network controllability Gramian to second-order network systems. Based on it, we develop an efficient method to compute H_2-norms and derive the approximation error between the full-order and reduced-order models. Finally, the approach is illustrated by the example of a small-world network.
Original languageEnglish
Pages (from-to)5026-5038
JournalIEEE Transactions on Automatic Control
Volume62
Issue number10
Publication statusPublished - Oct-2017

    Keywords

  • Large-scale system, Second-order Network systems, Structure-preserving model reduction, Network clustering, Graph simplification

Download statistics

No data available

ID: 40398207