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Four Encounters with System Identification
KTH, School of Electrical Engineering (EES), Automatic Control.ORCID iD: 0000-0002-9368-3079
2011 (English)In: European Journal of Control, ISSN 0947-3580, E-ISSN 1435-5671, Vol. 17, no 5-6, 449-471 p.Article in journal (Refereed) Published
Abstract [en]

Model-based engineering becomes more and more important in industrial practice. System identification is a vital technology for producing the necessary models, and has been an active area of research and applications in the automatic control community during half a century. At the same time, increasing demands require the area to constantly develop and sharpen its tools. This paper deals with how system identification does that by amalgamating concepts, features and methods from other fields. It describes encounters with four areas in systems theory and engineering: Networked Systems, Particle Filtering Techniques, Sparsity and Compressed Sensing, and Machine Learning. The impacts on System Identification methodology by these encounters are described and illustrated.

Place, publisher, year, edition, pages
2011. Vol. 17, no 5-6, 449-471 p.
Keyword [en]
Identification, networks, regularization, machine learning, Lasso
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:kth:diva-61006DOI: 10.3166/EJC.17.449-471ISI: 000298456800002Scopus ID: 2-s2.0-84055188727OAI: oai:DiVA.org:kth-61006DiVA: diva2:478444
Funder
EU, European Research Council, 267381
Note

QC 20120116

Available from: 2012-01-16 Created: 2012-01-16 Last updated: 2017-12-08Bibliographically approved

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Hjalmarsson, Håkan

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