• DocumentCode
    3436798
  • Title

    Contractions for consensus processes

  • Author

    Liu, J. ; Morse, A.S. ; Anderson, B.D.O. ; Yu, C.

  • Author_Institution
    Yale Univ., New Haven, CT, USA
  • fYear
    2011
  • fDate
    12-15 Dec. 2011
  • Firstpage
    1974
  • Lastpage
    1979
  • Abstract
    Many distributed control algorithms of current interest can be modeled by linear recursion equations of the form x(t + 1) = M(t)x(t), t ≥ 1 where each M(t) is a real-valued “stochastic” or “doubly stochastic” matrix. Convergence of such recursions often reduces to deciding when the sequence of matrix products M(1), M(2)M(1), M(3)M(2)M(1), ... converges. Certain types of stochastic and doubly stochastic matrices have the property that any sequence of products of such matrices of the form S1, S2S1, S3S2S1, ... converges exponentially fast. We explicitly characterize the largest classes of stochastic and doubly stochastic matrices with positive diagonal entries which have these properties. The main goal of this paper is to find a “semi-norm” with respect to which matrices from these “convergability classes” are contractions. For any doubly stochastic matrix S such a semi-norm is identified and is shown to coincide with the second largest singular value of S.
  • Keywords
    decentralised control; distributed control; matrix algebra; stochastic processes; consensus processes; distributed control algorithms; doubly stochastic matrix; linear recursion equations; matrix products; positive diagonal entries; Convergence; Eigenvalues and eigenfunctions; Equations; Mathematical model; Stochastic processes; Symmetric matrices; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control and European Control Conference (CDC-ECC), 2011 50th IEEE Conference on
  • Conference_Location
    Orlando, FL
  • ISSN
    0743-1546
  • Print_ISBN
    978-1-61284-800-6
  • Electronic_ISBN
    0743-1546
  • Type

    conf

  • DOI
    10.1109/CDC.2011.6160989
  • Filename
    6160989