• DocumentCode
    3348077
  • Title

    Failure detection and isolation in integrator networks

  • Author

    Rahimian, Mohammad Amin ; Preciado, Victor M.

  • Author_Institution
    Dept. of Electr. & Syst. Eng., Univ. of Pennsylvania, Philadelphia, PA, USA
  • fYear
    2015
  • fDate
    1-3 July 2015
  • Firstpage
    677
  • Lastpage
    682
  • Abstract
    Detection and isolation of link failures in directed networks of LTI systems have been the focus of our previous study. Our results relate the failure of links in the network to jump discontinuities in the derivatives of the output responses of the nodes and exploit this relation to propose failure detection and isolation (FDI) techniques, accordingly. In this work, we consider these results in the context of single-integrator networked dynamics, and show that with the additional niceties of the integrator networks and the enhanced proofs, one is able to incorporate both unidirectional and bidirectional link failures in our FDI algorithms. Computer experiments with large networks and both directed and undirected topologies provide interesting insights as to the role of directionality, as well as the scalability of the proposed FDI techniques with the network size.
  • Keywords
    directed graphs; failure analysis; linear systems; network theory (graphs); FDI technique; LTI system; bidirectional link failure; directed network; directionality; jump discontinuity; link failure detection; link failure isolation; network size; output response derivatives; single-integrator networked dynamics; undirected topology; unidirectional link failure; Artificial neural networks; Computational modeling; Computers; Heuristic algorithms; Image edge detection; Laplace equations; Linear systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference (ACC), 2015
  • Conference_Location
    Chicago, IL
  • Print_ISBN
    978-1-4799-8685-9
  • Type

    conf

  • DOI
    10.1109/ACC.2015.7170813
  • Filename
    7170813