Numerical conditioning and asymptotic variance of subspace estimates

DOI10.1016/j.automatica.2003.11.008zbMath1168.93411OpenAlexW2070297270MaRDI QIDQ1433070

Alessandro Chiuso, Giorgio Picci

Publication date: 15 June 2004

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.automatica.2003.11.008

zbMATH Keywords

subspace identificationasymptotic varianceoblique projectionscollinearityexogenous inputsnumerical conditioningstate-space identification

Mathematics Subject Classification ID

Related Items (6)

A novel subspace identification approach with passivity enforcement ⋮ On the ill-conditioning of subspace identification with inputs ⋮ Subspace identification by data orthogonalization and model decoupling ⋮ Asymptotic variance of subspace methods by data orthogonalization and model decoupling: a comparative analysis ⋮ Asymptotic properties of subspace estimators ⋮ Consistency analysis of some closed-loop subspace identification methods

Cites Work

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• Subspace identification by data orthogonalization and model decoupling
• Unit canonical correlations between future and past
• 4SID: Subspace algorithms for the identification of combined deterministic-stochastic systems
• The asymptotic variance of subspace estimates.
• On the ill-conditioning of subspace identification with inputs
• Some facts about the choice of the weighting matrices in Larimore type of subspace algorithms
• Analysis of the asymptotic properties of the MOESP type of subspace algorithms
• Subspace model identification Part 2. Analysis of the elementary output-error state-space model identification algorithm

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