• DocumentCode
    2186887
  • Title

    Asymptotic variances of subspace estimates

  • Author

    Chiuso, Alessandro ; Picci, Giorgio

  • Author_Institution
    Dipt. di Elettronica e Inf., Padova Univ., Italy
  • Volume
    4
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    3910
  • Abstract
    We provide new expressions for the asymptotic covariance of the estimated parameters (A, B, C, D) of a state space model obtained by some popular subspace identification method. The expressions, similar but simpler than the asymptotic covariance formulas which have so far been published in the literature, involve the inverses of the conditional covariance matrices Σ(xx|u+), Σ(u+u+|x) thus providing a direct link of possible ill-conditioning of the estimation problem with the asymptotic variance of the estimates. A study of ill-conditioning of subspace identification has been presented. The formulas can be applied to several subspace methods including N4SID, MOESP, CVA, etc
  • Keywords
    covariance matrices; linear systems; parameter estimation; state-space methods; stochastic systems; asymptotic covariance; covariance matrices; ill-conditioning; linear system; numerical conditioning; parameter estimation; state-space model; stochastic system; subspace identification; weighting matrix; Covariance matrix; Equations; Feedback; Parameter estimation; State estimation; State-space methods; System identification; Tail; Technological innovation; Yttrium;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 2001. Proceedings of the 40th IEEE Conference on
  • Conference_Location
    Orlando, FL
  • Print_ISBN
    0-7803-7061-9
  • Type

    conf

  • DOI
    10.1109/.2001.980485
  • Filename
    980485