Ritter, B. ; Schild, A. ; Feldt, M. ; Konigorski, U. (2024)
The design of nonlinear observers for wind turbine dynamic state and parameter estimation.
In: Journal of Physics: Conference Series, 2016, 753 (5)
doi: 10.26083/tuprints-00020876
Article, Secondary publication, Publisher's Version
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| Item Type: | Article |
|---|---|
| Type of entry: | Secondary publication |
| Title: | The design of nonlinear observers for wind turbine dynamic state and parameter estimation |
| Language: | English |
| Date: | 7 May 2024 |
| Place of Publication: | Darmstadt |
| Year of primary publication: | 2016 |
| Place of primary publication: | Bristol |
| Publisher: | IOP Publishing |
| Journal or Publication Title: | Journal of Physics: Conference Series |
| Volume of the journal: | 753 |
| Issue Number: | 5 |
| Collation: | 12 Seiten |
| DOI: | 10.26083/tuprints-00020876 |
| Corresponding Links: | |
| Origin: | Secondary publication DeepGreen |
| Abstract: | This contribution addresses the dynamic state and parameter estimation problem which arises with more advanced wind turbine controllers. These control devices need precise information about the system's current state to outperform conventional industrial controllers effectively. First, the necessity of a profound scientific treatment on nonlinear observers for wind turbine application is highlighted. Secondly, the full estimation problem is introduced and the variety of nonlinear filters is discussed. Finally, a tailored observer architecture is proposed and estimation results of an illustrative application example from a complex simulation set-up are presented. |
| Identification Number: | Artikel-ID: 052029 |
| Status: | Publisher's Version |
| URN: | urn:nbn:de:tuda-tuprints-208766 |
| Additional Information: | The Science of Making Torque from Wind (TORQUE 2016) |
| Classification DDC: | 500 Science and mathematics > 530 Physics 600 Technology, medicine, applied sciences > 621.3 Electrical engineering, electronics |
| Divisions: | 18 Department of Electrical Engineering and Information Technology > Institut für Automatisierungstechnik und Mechatronik |
| Date Deposited: | 07 May 2024 13:36 |
| Last Modified: | 17 May 2024 08:16 |
| SWORD Depositor: | Deep Green |
| URI: | https://tuprints.ulb.tu-darmstadt.de/id/eprint/20876 |
| PPN: | 51802489X |
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