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
Link To Document