• DocumentCode
    2878801
  • Title

    Closed loop subspace system identification

  • Author

    Van Overschee, Peter ; De Moor, Bart

  • Author_Institution
    ESAT, Katholieke Univ., Leuven, Heverlee, Belgium
  • Volume
    2
  • fYear
    1997
  • fDate
    10-12 Dec 1997
  • Firstpage
    1848
  • Abstract
    We present a general framework for closed loop subspace system identification. This framework consists of two new projection theorems which allow the extraction of non-steady state Kalman filter states and of system related matrices directly from input output data. Three algorithms for the identification of the state space matrices can be derived from these theorems. The similarities between the theorems and algorithms, and the corresponding open loop theorems and algorithms in the literature are remarked on
  • Keywords
    Hankel matrices; Kalman filters; Toeplitz matrices; closed loop systems; controllability; state estimation; state-space methods; closed loop subspace system identification; nonsteady state Kalman filter states; projection theorems; state space matrices; Data mining; Error correction; Feedback; Instruments; Intelligent systems; MIMO; Optimal control; Optimization methods; State-space methods; System identification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 1997., Proceedings of the 36th IEEE Conference on
  • Conference_Location
    San Diego, CA
  • ISSN
    0191-2216
  • Print_ISBN
    0-7803-4187-2
  • Type

    conf

  • DOI
    10.1109/CDC.1997.657851
  • Filename
    657851