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Distributed system identification with ADMM
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
2014 (English)In: Proceedings of the 53rd IEEE Conference on Decision and Control, Los Angeles, 2014, 290-295 p.Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents identification of both network connected systems as well as distributed systems governed by PDEs in the framework of distributed optimization via the Alternating Direction Method of Multipliers. This approach opens first the possibility to identify distributed models in a global manner using all available data sequences and second the possibility for a distributed implementation. The latter will make the application to large scale complex systems possible. In addition to outlining a new large scale identification method, illustrations are shown for identifying both network connected systems and discretized PDEs.

Place, publisher, year, edition, pages
Los Angeles, 2014. 290-295 p.
Series
53rd IEEE Conference on Decision and Control, ISSN 0191-2216
National Category
Computer Science
Identifiers
URN: urn:nbn:se:liu:diva-129292DOI: 10.1109/CDC.2014.7039396ISBN: 978-1-4799-7745-1 (print)ISBN: 978-1-4673-6088-3 (print)OAI: oai:DiVA.org:liu-129292DiVA: diva2:937576
Conference
53rd IEEE Conference on Decision and Control 15-17 Dec. 2014, Los Angeles, CA
Available from: 2016-06-15 Created: 2016-06-15 Last updated: 2016-06-29

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CiteExportLink to record
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