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Identifiability and Observability Assessment for Nonlinear Wind Turbine Control Systems

Schmitt, Thomas (2017)
Identifiability and Observability Assessment for Nonlinear Wind Turbine Control Systems.
Technische Universität Darmstadt
Masterarbeit, Erstveröffentlichung

Kurzbeschreibung (Abstract)

This work investigates the identifiability and observability of two nonlinear wind turbine models. Various definitions of both concepts are summarized together with an interpretation of their relation. An overview of existing methods to assess the identifiability and observability of nonlinear systems qualitatively as well as quantitatively is given. Of these, the profile likelihood approach is chosen and applied to both models. Thereby, statistical confidence intervals for parameters and states are derived. The identifiability of the air density, eigenfrequency and wind velocity as well as the observability of all states is assessed for various wind scenarios and measurement configurations. A qualitative overview is given together with a detailed analysis for selected constellations. Furthermore, the validity of the used methodology is verified.

Typ des Eintrags: Masterarbeit
Erschienen: 2017
Autor(en): Schmitt, Thomas
Art des Eintrags: Erstveröffentlichung
Titel: Identifiability and Observability Assessment for Nonlinear Wind Turbine Control Systems
Sprache: Englisch
Referenten: Konigorski, Prof. Dr. Ulrich ; Ritter, M. Sc. Bastian
Publikationsjahr: 30 November 2017
Ort: Darmstadt
Datum der mündlichen Prüfung: 19 Dezember 2017
URL / URN: https://tuprints.ulb.tu-darmstadt.de/9264
Kurzbeschreibung (Abstract):

This work investigates the identifiability and observability of two nonlinear wind turbine models. Various definitions of both concepts are summarized together with an interpretation of their relation. An overview of existing methods to assess the identifiability and observability of nonlinear systems qualitatively as well as quantitatively is given. Of these, the profile likelihood approach is chosen and applied to both models. Thereby, statistical confidence intervals for parameters and states are derived. The identifiability of the air density, eigenfrequency and wind velocity as well as the observability of all states is assessed for various wind scenarios and measurement configurations. A qualitative overview is given together with a detailed analysis for selected constellations. Furthermore, the validity of the used methodology is verified.

URN: urn:nbn:de:tuda-tuprints-92643
Fachbereich(e)/-gebiet(e): 18 Fachbereich Elektrotechnik und Informationstechnik
18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Automatisierungstechnik und Mechatronik
18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Automatisierungstechnik und Mechatronik > Regelungstechnik und Mechatronik
Hinterlegungsdatum: 10 Nov 2019 20:55
Letzte Änderung: 10 Nov 2019 20:55
PPN:
Referenten: Konigorski, Prof. Dr. Ulrich ; Ritter, M. Sc. Bastian
Datum der mündlichen Prüfung / Verteidigung / mdl. Prüfung: 19 Dezember 2017
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