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Variance Analysis in SISO Linear Systems Identification
KTH, School of Electrical Engineering (EES), Automatic Control.ORCID iD: 0000-0002-3672-5316
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. (System Identification)ORCID iD: 0000-0002-9368-3079
2015 (English)In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836Article in journal (Refereed) Submitted
Abstract [en]

Causal single input single output linear time invariant systems are considered. Expressions for the asymptotic (co)variance of system properties estimated using the prediction error method are derived. These expressions delineate the impacts of model structure, model order, true system dynamics, and experimental conditions. A connection to results on frequency function estimation is established. Also, simple model structure independent upper bounds are derived. Explicit variance expressions and bounds are provided for common system properties such as impulse response coefficients and non-minimum phase zeros. As an illustration of the insights the expressions provide, they are used to derive conditions on the input spectrum which makethe asymptotic variance of non-minimum phase zero estimates independent of the model order and model structure.

Place, publisher, year, edition, pages
2015.
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-159099OAI: oai:DiVA.org:kth-159099DiVA: diva2:782528
Funder
Swedish Research Council, 621-2007-6271Swedish Research Council, 621-2009-4017
Note

NQC 2015

Available from: 2015-01-21 Created: 2015-01-21 Last updated: 2017-12-05Bibliographically approved

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Mårtensson, JonasEveritt, NiklasHjalmarsson, Håkan

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