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Frequency domain identification of ARX models in the presence of additive input–output noise
Department of Electrical, Electronic and Information Engineering, University of Bologna, Italy.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.ORCID iD: 0000-0003-4619-8879
2017 (English)In: 20th IFAC World Congress, Elsevier, 2017, Vol. 50, p. 6226-6231Conference paper, Published paper (Refereed)
Abstract [en]

This paper describes a new approach for identifying ARX models from a finite number of measurements, in presence of additive and uncorrelated white noise. The proposed algorithm is based on some theoretical results concerning the so-called dynamic Frisch Scheme. As a major novelty, the proposed approach deals with frequency domain data. In some aspects, the method resembles the characteristics of other identification algorithms, originally developed in the time domain. The proposed method is compared with other techniques by means of Monte Carlo simulations. The benefits of filtering the data and using only part of the frequency domain is highlighted by means of a numerical example.

Place, publisher, year, edition, pages
Elsevier, 2017. Vol. 50, p. 6226-6231
Series
IFAC-PapersOnLine, E-ISSN 2405-8963 ; 50: 1
National Category
Signal Processing
Research subject
Electrical Engineering with specialization in Automatic Control
Identifiers
URN: urn:nbn:se:uu:diva-334132DOI: 10.1016/j.ifacol.2017.08.1023ISI: 000423964900038OAI: oai:DiVA.org:uu-334132DiVA, id: diva2:1158786
Conference
20th World Congress of the International-Federation-of-Automatic-Control (IFAC),Toulouse, France, July 09-14, 2017.
Available from: 2017-11-21 Created: 2017-11-21 Last updated: 2018-05-16Bibliographically approved

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Söderström, Torsten

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