Connections between L2-Model Reduction and Balanced Truncation
2003 (English)In: Proceedings of the 13th Symposium on System Identfication, 2003, 1849-1854 p.Conference paper (Refereed)
In this paper we investigate the connection between model reduction by balanced truncation and by L2 reduction. We show that locally, i.e., close to the set of lower order systems, balanced truncation and (un-weighted) L2 model reduction produce models that are almost identical. This implies that high order estimated models can be reduced by either L2 reduction or balanced truncation, both methods giving a low order model with the same asymptotic varaiance, if the true data generating model is in the class of low order models.
Place, publisher, year, edition, pages
2003. 1849-1854 p.
Model reduction, Balanced truncation, L2 reduction, System identification
Engineering and Technology Control Engineering
IdentifiersURN: urn:nbn:se:liu:diva-90819ISBN: 9780080437095OAI: oai:DiVA.org:liu-90819DiVA: diva2:616338
13th Symposium on System Identification, Rotterdam, The Netherlands, August, 2003