• DocumentCode
    359042
  • Title

    Identification of subsonic jet by dynamical recursive neural network and validation by Lyapunov exponents

  • Author

    Djamaï, L. ; Coirault, P. ; Mehdi, D.

  • Author_Institution
    Lab. d´´Autom. et d´´Inf. Ind., Ecole Superieure d´´Ingenieurs de Poiters, France
  • Volume
    3
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    1710
  • Abstract
    The goal of this article is to identify a subsonic jet model generated in an industrial wind tunnel (blower) from actual measurements of the speed. For that, a new phase space is constructed by delay method (MOD). This construction enables one to extract invariants from the system. The identification based on a dynamical recursive neural network uses the time series of measurement. The validation of the model is achieved if the invariants resulting from the real system and those resulting from the model are nearly identical
  • Keywords
    Lyapunov methods; jets; neural nets; phase space methods; recursive estimation; subsonic flow; time series; Lyapunov exponent validation; MOD; blower; delay method; dynamical recursive neural network; industrial wind tunnel; measurement time series; model validation; phase space; subsonic jet identification; Chaos; Delay effects; Fluid flow measurement; Jacobian matrices; Neural networks; Phase measurement; Robustness; Solid modeling; Time measurement; Velocity measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference, 2000. Proceedings of the 2000
  • Conference_Location
    Chicago, IL
  • ISSN
    0743-1619
  • Print_ISBN
    0-7803-5519-9
  • Type

    conf

  • DOI
    10.1109/ACC.2000.879493
  • Filename
    879493