Identification of errors in variables linear state space models using iterative principal component analysis

DOI10.1080/00207179.2022.2112089zbMath1526.93029OpenAlexW4290975515MaRDI QIDQ6076627

Unnamed Author, Shankar Narasimhan

Publication date: 17 October 2023

Published in: International Journal of Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207179.2022.2112089

zbMATH Keywords

system identificationprincipal component analysisstate space modelsubspace-based identificationerrors-in-variables approach

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) System identification (93B30)

Cites Work

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• On-line modified least-squares parameter estimation of linear discrete dynamic systems
• Algorithms for recursive/semi-recursive bias-compensating least squares system identification within the errors-in-variables framework
• Identification of EIV models by compensated PEM
• A generalised instrumental variable estimator for multivariable errors-in-variables identification problems
• Errors-in-variables methods in system identification

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