Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Subspace Hammerstein Model Identification under Periodic Disturbance
KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.ORCID iD: 0000-0002-1927-1690
KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.ORCID iD: 0000-0002-6855-5868
2018 (English)Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, a subspace identification method is proposed for Hammerstein systems under periodic disturbance. By using the linear superposition principle to decompose the periodic disturbance response from the deterministic system response, an orthogonal projection is established to eliminate the disturbance effect. The unknown disturbance period can be estimated by defining an objective function of output prediction error for minimization. Correspondingly, a singular value decomposition (SVD) based algorithm is given to estimate the observability matrix and the lower triangular block-Toeplitz matrix. The state matrices A and C are subsequently retrieved from the estimated observability matrix via a shift-invariant algorithm, while the input matrix B and the nonlinear input function parameters are retrieved from the estimated lower triangular block-Toeplitz matrix by an SVD approach. Consistent estimation of the observability matrix and the lower triangular block-Toeplitz matrix is analyzed. An illustrative example is shown to demonstrate the effectiveness of the proposed identification method. 

Place, publisher, year, edition, pages
Elsevier B.V. , 2018. Vol. 51, no 15, p. 335-340
Keywords [en]
Consistent estimation, Hammerstein system, Periodic disturbance, Subspace identification, Identification (control systems), Nonlinear systems, Observability, Block Toeplitz matrices, Linear superposition principles, Output prediction errors, Periodic disturbances, Subspace identification methods, Singular value decomposition
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-247499DOI: 10.1016/j.ifacol.2018.09.157ISI: 000446599200058Scopus ID: 2-s2.0-85054358180OAI: oai:DiVA.org:kth-247499DiVA, id: diva2:1301976
Conference
18th IFAC Symposium on System Identification SYSID 2018
Note

QC 20190403

Available from: 2019-04-03 Created: 2019-04-03 Last updated: 2019-05-20Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records BETA

Wahlberg, BoJansson, Magnus

Search in DiVA

By author/editor
Wahlberg, BoJansson, Magnus
By organisation
Automatic ControlInformation Science and Engineering
Control Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 85 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf