Variance Aspects of L2 Model Reduction when Undermodeling - the Output Error Case
2002 (English)In: Proceedings of the 15th IFAC World Congress, 2002, 453-453 p.Conference paper (Refereed)
In this contribution, variance properties of L2 model reduction are studied. That is, given an estimated model of high order we study the resulting variance of an L2 reduced approximation. The main result of the paper is showing that estimating a low order output error (OE) model via L2 model reduction of a high order model gives a smaller variance compared to estimating a low order model directly from data in the case of undermodeling. This has previously been shown to hold for FIR (Finite Impulse Response) models, but is in this paper extended to general linear OE models.
Place, publisher, year, edition, pages
2002. 453-453 p.
System identification, Model reduction, Modeling errors, Covariance, System order reduction, Output error identification
Engineering and Technology Control Engineering
IdentifiersURN: urn:nbn:se:liu:diva-90271DOI: 10.3182/20020721-6-ES-1901.00455ISBN: 978-3-902661-74-6OAI: oai:DiVA.org:liu-90271DiVA: diva2:614245
15th IFAC World Congress, Barcelona, Spain, July, 2002