Automatica, Vol.40, No.10, 1705-1717, 2004
Asymptotic variance of subspace methods by data orthogonalization and model decoupling: a comparative analysis
This is a companion of the paper Chiuso and Picci (2004d) where we do asymptotic error analysis of a weighted PI-MOESP type method and compare accuracy with respect to estimates obtained by customary "joint" subspace methods. The analysis shows that, under certain conditions, methods based on orthogonal decomposition of the input-output data and block-decoupled parametrization perform better than traditional joint-model based methods in the circumstance of nearly parallel regressors. (C) 2004 Elsevier Ltd. All rights reserved.
Keywords:subspace identification;exogenous inputs;stochastic realization;statistical analysis;stochastic state-space identification