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Perspectives on System Identification
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2010 (English)Report (Other academic)
Abstract [en]

System identification is the art and science of building mathematical models of dynamic systems from observed input-output data. It can be seen as the interface between the real world of applications and the mathematical world of control theory and model abstractions. As such, it is an ubiquitous necessity for successful applications. System identification is a very large topic, with different techniques that depend on the character of the models to be estimated: linear, nonlinear, hybrid, nonparametric etc. At the same time, the area can be characterized by a small number of leading principles, e.g. to look for sustainable descriptions by proper decisions in the triangle of model complexity, information contents in the data, and effective validation. The area has many facets and there are many approaches and methods. A tutorial or a survey in a few pages is not quite possible. Instead, this presentation aims at giving an overview of the "science" side, i.e. basic principles and results and at pointing to open problem areas in the practical, "art", side of how to approach and solve a real problem.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2010. , 17 p.
Series
LiTH-ISY-R, ISSN 1400-3902 ; 2989
Keyword [en]
Nonlinear system identification- -Subspace methods--Identification for control--Grey-box modeling
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-97743ISRN: LiTH-ISY-R-2989OAI: oai:DiVA.org:liu-97743DiVA: diva2:650670
Projects
CADICS
Available from: 2013-09-23 Created: 2013-09-23 Last updated: 2014-09-01Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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Output format
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