• DocumentCode
    175714
  • Title

    Gain estimates and exponential ISS for a class of hybrid dynamical networks

  • Author

    Bin Liu ; Chunxia Dou ; Dong-Nan Liu

  • Author_Institution
    Coll. of Sci., Hunan Univ. of Technol., Zhuzhou, China
  • fYear
    2014
  • fDate
    May 31 2014-June 2 2014
  • Firstpage
    985
  • Lastpage
    990
  • Abstract
    This paper studies the exponential input-to-state stability (e-ISS) for hybrid dynamical networks (HDNs) consisting of flow and jumping subsystems. Concepts of input-to-state exponent (IS-E) and event-ISS are proposed. By using the IS-E estimates of subsystems and the method of multiple Lyapunov functions and M-matrix theory, the e-ISS including event-e-ISS criteria are established for HDNs. The small-gain condition for the coupling of flows is needed while such condition for the coupling of impulses is not necessary. It also shows that a HDN may have ISS even all subsystems have no ISS. Finally, one example is given to illustrate the results.
  • Keywords
    Lyapunov methods; asymptotic stability; input-output stability; matrix algebra; HDN; IS-E estimates; Lyapunov functions; M-matrix theory; event-e-ISS criteria; exponential ISS; exponential input-to-state stability; flow coupling; flow subsystems; gain estimates; hybrid dynamical networks; input-to-state exponent; jumping subsystems; small-gain condition; Couplings; Educational institutions; Lyapunov methods; Silicon; Stability criteria; Switches; Input-to-state stability (ISS); M-matrix; hybrid dynamical network; multiple Lyapunov functions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference (2014 CCDC), The 26th Chinese
  • Conference_Location
    Changsha
  • Print_ISBN
    978-1-4799-3707-3
  • Type

    conf

  • DOI
    10.1109/CCDC.2014.6852307
  • Filename
    6852307