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Söderström, TorstenORCID iD iconorcid.org/0000-0003-4619-8879
Alternative names
Publications (10 of 229) Show all publications
Söderström, T. & Soverini, U. (2022). When Are Errors-in-Variables Aspects Important to Consider in System Identification?. In: 2022 European Control Conference (ECC): . Paper presented at European Control Conference (ECC), July 12-15, 2022, London, England (pp. 315-320). Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>When Are Errors-in-Variables Aspects Important to Consider in System Identification?
2022 (English)In: 2022 European Control Conference (ECC), Institute of Electrical and Electronics Engineers (IEEE), 2022, p. 315-320Conference paper, Published paper (Refereed)
Abstract [en]

When recorded signals are corrupted by noise on both input and output sides, standard identification methods give biased parameter estimates, due to the presence of input noise. This paper discusses in what situations such a bias is large and, consequently, when errors-in-variables identification methods should preferably be used.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2022
Keywords
system identification, errors-in-variables, bias, parameter estimation, output error model
National Category
Control Engineering
Identifiers
urn:nbn:se:uu:diva-487624 (URN)10.23919/ECC55457.2022.9838030 (DOI)000857432300042 ()978-3-907144-07-7 (ISBN)978-1-6654-9733-6 (ISBN)
Conference
European Control Conference (ECC), July 12-15, 2022, London, England
Available from: 2022-11-04 Created: 2022-11-04 Last updated: 2023-05-02Bibliographically approved
Soverini, U. & Söderström, T. (2020). Blind identification of two-channel FIR systems: a frequency domain approach. In: IFAC PapersOnline: . Paper presented at 21st IFAC World Congress on Automatic Control - Meeting Societal Challenges, JUL 11-17, 2020, ELECTR NETWORK (pp. 914-920). Elsevier BV, 53(2)
Open this publication in new window or tab >>Blind identification of two-channel FIR systems: a frequency domain approach
2020 (English)In: IFAC PapersOnline, Elsevier BV , 2020, Vol. 53, no 2, p. 914-920Conference paper, Published paper (Refereed)
Abstract [en]

This paper describes a new approach for the blind identification of a two-channel FIR system from a finite number of output measurements, in the presence of additive and uncorrelated white noise. The proposed approach is based on frequency domain data and, as a major novelty, it enables the estimation to be frequency selective. The features of the proposed method are analyzed by means of Monte Carlo simulations. The benefits of filtering the data and using only part of the frequency domain are highlighted by means of a numerical example.

Place, publisher, year, edition, pages
Elsevier BV, 2020
Keywords
Blind identification, FIR systems, Discrete Fourier Transform
National Category
Signal Processing Control Engineering
Identifiers
urn:nbn:se:uu:diva-447685 (URN)10.1016/j.ifacol.2020.12.855 (DOI)000652592500148 ()
Conference
21st IFAC World Congress on Automatic Control - Meeting Societal Challenges, JUL 11-17, 2020, ELECTR NETWORK
Available from: 2021-06-29 Created: 2021-06-29 Last updated: 2021-06-29Bibliographically approved
Soverini, U. & Söderström, T. (2020). Frequency domain identification of FIR models in the presence of additive input-output noise. Automatica, 115, Article ID 108879.
Open this publication in new window or tab >>Frequency domain identification of FIR models in the presence of additive input-output noise
2020 (English)In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 115, article id 108879Article in journal (Refereed) Published
Abstract [en]

This paper describes a new approach for identifying FIR models from a finite number of measurements, in the presence of additive and uncorrelated white noise. In particular, two different frequency domain algorithms are proposed. The first algorithm is based on some theoretical results concerning the dynamic Frisch scheme. The second algorithm maps the FIR identification problem into a quadratic eigenvalue problem. Both methods resemble in many aspects some other identification algorithms, originally developed in the time domain. The features of the proposed methods are compared with each other and with those of some time domain algorithms by means of Monte Carlo simulations.

Place, publisher, year, edition, pages
PERGAMON-ELSEVIER SCIENCE LTD, 2020
Keywords
System identification, FIR models, Discrete Fourier transform
National Category
Control Engineering
Identifiers
urn:nbn:se:uu:diva-410883 (URN)10.1016/j.automatica.2020.108879 (DOI)000525865500026 ()
Available from: 2020-05-26 Created: 2020-05-26 Last updated: 2020-05-26Bibliographically approved
Soverini, U. & Söderström, T. (2020). The Frisch scheme for EIV system identification: time and frequency domain formulations. In: IFAC PapersOnline: . Paper presented at 21st IFAC World Congress on Automatic Control - Meeting Societal Challenges, JUL 11-17, 2020, ELECTR NETWORK (pp. 907-913). Elsevier BV, 53(2)
Open this publication in new window or tab >>The Frisch scheme for EIV system identification: time and frequency domain formulations
2020 (English)In: IFAC PapersOnline, Elsevier BV , 2020, Vol. 53, no 2, p. 907-913Conference paper, Published paper (Refereed)
Abstract [en]

Several estimation methods have been proposed for identifying errors-in-variables systems, where both input and output measurements are corrupted by noise. One of the more interesting approaches is the Frisch scheme. The method can be applied using either time or frequency domain representations. This paper investigates the general mathematical and geometrical aspects of the Frisch scheme, illustrating the analogies and the differences between the time and frequency domain formulations.

Place, publisher, year, edition, pages
Elsevier BV, 2020
Keywords
System identification, EIV models, Frisch scheme, Discrete Fourier Transform
National Category
Signal Processing Control Engineering
Identifiers
urn:nbn:se:uu:diva-447686 (URN)10.1016/j.ifacol.2020.12.851 (DOI)000652592500147 ()
Conference
21st IFAC World Congress on Automatic Control - Meeting Societal Challenges, JUL 11-17, 2020, ELECTR NETWORK
Available from: 2021-06-29 Created: 2021-06-29 Last updated: 2021-06-29Bibliographically approved
Verbeke, D., Söderström, T. & Soverini, U. (2019). A note on the estimation of real- and complex-valued parameters in frequency domain maximum likelihood identification. Automatica, 110, Article ID 108584.
Open this publication in new window or tab >>A note on the estimation of real- and complex-valued parameters in frequency domain maximum likelihood identification
2019 (English)In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 110, article id 108584Article in journal (Refereed) Published
Abstract [en]

Recently, maximum likelihood estimators were derived for frequency domain identification of linear time-invariant models with Gaussian input output uncertainty. This note draws attention to an issue that arises in one of the steps in the optimization of the likelihood function.

Keywords
Errors-in-variables, Maximum likelihood, Frequency domain, Linear time-invariant dynamical systems
National Category
Control Engineering
Identifiers
urn:nbn:se:uu:diva-397962 (URN)10.1016/j.automatica.2019.108584 (DOI)000495491900023 ()
Available from: 2019-12-06 Created: 2019-12-06 Last updated: 2019-12-06Bibliographically approved
Söderström, T. (2019). A user perspective on errors-in-variables methods in system identification. Control Engineering Practice, 89, 56-69
Open this publication in new window or tab >>A user perspective on errors-in-variables methods in system identification
2019 (English)In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 89, p. 56-69Article in journal (Refereed) Published
National Category
Control Engineering
Identifiers
urn:nbn:se:uu:diva-392575 (URN)10.1016/j.conengprac.2019.05.013 (DOI)000477785800005 ()
Available from: 2019-05-30 Created: 2019-09-09 Last updated: 2019-09-20Bibliographically approved
Soverini, U. & Söderström, T. (2018). 2D-frequency domain identification of complex sinusoids in the presence of additive noise. In: : . Paper presented at SYSID 2018, July 9–11, Stockholm, Sweden (pp. 820-825). (15)
Open this publication in new window or tab >>2D-frequency domain identification of complex sinusoids in the presence of additive noise
2018 (English)Conference paper, Published paper (Refereed)
Series
IFAC-PapersOnLine, ISSN 2405-8963 ; 51:15
National Category
Control Engineering Signal Processing
Identifiers
urn:nbn:se:uu:diva-366232 (URN)10.1016/j.ifacol.2018.09.125 (DOI)000446599200139 ()
Conference
SYSID 2018, July 9–11, Stockholm, Sweden
Available from: 2018-10-08 Created: 2018-11-18 Last updated: 2018-12-14Bibliographically approved
Söderström, T. (2018). Errors-in-Variables Methods in System Identification. Springer
Open this publication in new window or tab >>Errors-in-Variables Methods in System Identification
2018 (English)Book (Refereed)
Place, publisher, year, edition, pages
Springer, 2018
National Category
Control Engineering
Identifiers
urn:nbn:se:uu:diva-366234 (URN)10.1007/978-3-319-75001-9 (DOI)978-3-319-75000-2 (ISBN)
Available from: 2018-11-18 Created: 2018-11-18 Last updated: 2018-12-07Bibliographically approved
Soverini, U. & Söderström, T. (2018). Identification of two-dimensional complex sinusoids in white noise: a state-space frequency approach. In: : . Paper presented at SYSID 2018, July 9–11, Stockholm, Sweden (pp. 996-1001). (15)
Open this publication in new window or tab >>Identification of two-dimensional complex sinusoids in white noise: a state-space frequency approach
2018 (English)Conference paper, Published paper (Refereed)
Series
IFAC-PapersOnLine, ISSN 2405-8963 ; 51:15
National Category
Control Engineering
Identifiers
urn:nbn:se:uu:diva-366284 (URN)10.1016/j.ifacol.2018.09.064 (DOI)000446599200168 ()
Conference
SYSID 2018, July 9–11, Stockholm, Sweden
Available from: 2018-10-08 Created: 2018-11-19 Last updated: 2018-12-14Bibliographically approved
Söderström, T. & Soverini, U. (2017). Errors-in-variables identification using maximum likelihood estimation in the frequency domain. Automatica, 79, 131-143
Open this publication in new window or tab >>Errors-in-variables identification using maximum likelihood estimation in the frequency domain
2017 (English)In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 79, p. 131-143Article in journal (Refereed) Published
National Category
Control Engineering
Identifiers
urn:nbn:se:uu:diva-322085 (URN)10.1016/j.automatica.2017.01.016 (DOI)000399513300017 ()
Available from: 2017-03-02 Created: 2017-05-16 Last updated: 2017-05-17Bibliographically approved
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ORCID iD: ORCID iD iconorcid.org/0000-0003-4619-8879

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