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 :
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