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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