On the use of minimal parametrisations in multivariable ARMAX identification

DOI10.1016/S0947-3580(98)70103-7zbMath0914.93016OpenAlexW1992291988MaRDI QIDQ1267250

Roberto P. Guidorzi

Publication date: 6 October 1998

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

Full work available at URL: https://doi.org/10.1016/s0947-3580(98)70103-7

zbMATH Keywords

orderlinear multivariable systemsstructureprediction error identificationARMAX predictorsminimally parameterized ARMAX modelsnon-identifiability conditions

Mathematics Subject Classification ID

System identification (93B30) Multivariable systems, multidimensional control systems (93C35) Canonical structure (93B10) Minimal systems representations (93B20)

Cites Work

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• On covariance function tests used in system identification
• Uniquely identifiable state-space and ARMA parametrizations for multivariable linear systems
• Time series in the time domain
• Estimation of vector Armax models
• Invariants and canonical forms for systems structural and parametric identification
• Canonical structures in the identification of multivariable systems
• Multivariate linear time series models
• ARMA models, their Kronecker indices and their McMillan degree
• Some numerical aspects of multivariable systems identification

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