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Initialisation Aspects for Subspace and Output-Error Identification Methods
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2003 (English)In: Proceedings of the 2003 European Control Conference, 2003Conference paper, Published paper (Refereed)
Abstract [en]

This paper is inspired by a recent contribution by Rao and Garnier about identification of continuous time models. They show examples where methods that directly estimate continuous time models, based on smoothed differentiated input-output data outperform methods that are based on discrete time model estimation. The reasons for that situation are investigated in this contribution. It turns out that the key problem is that ARX-type models are very biased for the example in that study, which leads to problems for initializations for output error models both based on ARX/IV techniques and on subspace (CVA estimation techniques). The remedy is to decrease the ARX-bias via low pass data filtering, which in turn also explains why the direct continuous-time estimation techniques (with inherent data smoothing) do not suffer from this problem.

Place, publisher, year, edition, pages
2003.
Keyword [en]
System identification, Subspace techniques, ARX models, Continuous-time model estimation
National Category
Engineering and Technology Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-90862OAI: oai:DiVA.org:liu-90862DiVA: diva2:615052
Conference
2003 European Control Conference, Cambridge, United Kingdom, September, 2003
Available from: 2013-04-08 Created: 2013-04-07 Last updated: 2013-04-08

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