• DocumentCode
    574350
  • Title

    Combinatorial insights and robustness analysis for clustering in dynamical networks

  • Author

    Burger, M. ; Zelazo, D. ; Allgower, F.

  • Author_Institution
    Inst. for Syst. Theor. & Autom. Control, Univ. of Stuttgart, Stuttgart, Germany
  • fYear
    2012
  • fDate
    27-29 June 2012
  • Firstpage
    454
  • Lastpage
    459
  • Abstract
    This paper studies a clustering phenomena that emerges from a dynamic network with bounded and non-linear interactions. Necessary and sufficient conditions are given describing when the network exhibits clustering. We introduce a synchronization coefficient to quantify whether a network is synchronizing or clustering and provide a robustness margin for clustering. A combinatorial description of the dynamic network clustering is provided that relates to optimal graph partitioning. Finally, the synchronization coefficient is also used for defining a set of critical disturbances that can cause the system to cluster.
  • Keywords
    graph theory; large-scale systems; nonlinear control systems; pattern clustering; robust control; synchronisation; bounded interaction; clustering phenomena; combinatorial description; combinatorial insight; complex dynamical network; critical disturbance; dynamic network clustering; nonlinear interaction; optimal graph partitioning; robustness analysis; robustness margin; synchronization coefficient; Optimization; Power system dynamics; Robustness; Steady-state; Synchronization; Trajectory; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference (ACC), 2012
  • Conference_Location
    Montreal, QC
  • ISSN
    0743-1619
  • Print_ISBN
    978-1-4577-1095-7
  • Electronic_ISBN
    0743-1619
  • Type

    conf

  • DOI
    10.1109/ACC.2012.6314935
  • Filename
    6314935