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MOOSE2—A toolbox for least-costly application-oriented input design
KTH, School of Electrical Engineering (EES), Automatic Control.
2016 (English)In: SoftwareX, ISSN 2352-7110, Vol. 5, 96-100 p.Article in journal (Refereed) Published
Abstract [en]

MOOSE2 is a MATLAB®-based toolbox for solving least-costly application-oriented input design problems in system identification. MOOSE2 provides the spectrum of the input signal to be used in the identification experiment made to estimate a linear parametric model of the system. The objective is to find a spectrum that minimizes experiment cost while fulfilling constraints imposed in the experiment and on the obtained model. The constraints considered by MOOSE2 are: frequency or power constraints on the signal spectra in the experiment, and application or quality specifications on the obtained model.

Place, publisher, year, edition, pages
Elsevier, 2016. Vol. 5, 96-100 p.
Keyword [en]
Input design, MATLAB®, System identification
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:kth:diva-201979DOI: 10.1016/j.softx.2016.05.003ScopusID: 2-s2.0-85006507406OAI: oai:DiVA.org:kth-201979DiVA: diva2:1078355
Note

Funding text: The research leading up to this work was partly funded by the Swedish Research Council under contract 621-2009-4017, the European Union's Seventh Framework Programme (FP7/2007–2013) under grant agreement no 257059 (Autoprofit), and the European Research Council under the advanced grant LEARN, contract 267381. The authors would also like to thank Henrik Jansson (Ph.D.) and Märta Barenthin Sydberg (Ph.D.) for their research and collection of MATLAB

QC 20170303

Available from: 2017-03-03 Created: 2017-03-03 Last updated: 2017-03-03Bibliographically approved

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