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Identification of Unstable Systems using Output Error and Box-Jenkins Model Structures
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2000 (English)In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 45, no 1, 131-147 p.Article in journal (Refereed) Published
Abstract [en]

It is well known that the output error and Box-Jenkins model structures cannot be used for prediction error identification of unstable systems. The reason for this is that the predictors in this case generically will be unstable. Typically, this problem is handled by projecting the parameter vector onto the region of stability, which gives erroneous results when the underlying system is unstable. The main contribution of this work is that we derive modified, but asymptotically equivalent, versions of these model structures that can also be applied in the case of unstable systems.

Place, publisher, year, edition, pages
2000. Vol. 45, no 1, 131-147 p.
Keyword [en]
Autoregressive moving average processes, Closed loop systems, Filtering theory, Identification, Prediction theory
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-56369DOI: 10.1109/9.827371OAI: oai:DiVA.org:liu-56369DiVA: diva2:318579
Available from: 2010-05-08 Created: 2010-05-07 Last updated: 2017-12-12

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Ljung, Lennart

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