• DocumentCode
    3548800
  • Title

    Unknown Input Detection Using Receding Horizon Approach

  • Author

    Kulcsár, Balázs ; Bokor, József

  • Author_Institution
    Dept. of Transp. Autom., Budapest Univ. of Technol. & Econ.
  • fYear
    2005
  • fDate
    27-29 June 2005
  • Firstpage
    423
  • Lastpage
    428
  • Abstract
    The paper offers the possibility of the design of unknown input detection for dynamic systems under external noise effect. The presented geometric based fundamental problem in residual generation (FPRG) method uses on the one hand the Kalman filtering and on the other hand the moving horizon estimation (MHE) when stochastic noise on the input and on the output, with additive failure directions, are presents. The paper combines the optimal Kalman and MHE method with geometric based unknown input observer strategy. The MHE solution makes to treat constraints during the estimation process possible. A numerical example supports the necessity of constrained unknown input estimation
  • Keywords
    Kalman filters; fault location; noise; observers; time-varying systems; Kalman filtering; dynamic system; external noise effect; fundamental problem in residual generation method; moving horizon estimation; receding horizon approach; stochastic noise; unknown input detection; unknown input observer strategy; Additive noise; Automation; Control systems; Fault detection; Kalman filters; Predictive control; Predictive models; Space technology; Stability; State estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control, 2005. Proceedings of the 2005 IEEE International Symposium on, Mediterrean Conference on Control and Automation
  • Conference_Location
    Limassol
  • ISSN
    2158-9860
  • Print_ISBN
    0-7803-8936-0
  • Type

    conf

  • DOI
    10.1109/.2005.1467052
  • Filename
    1467052