Höhl, Andreas ; Maiworm, Michael ; Findeisen, Rolf (2023)
Path Following or Tracking Model Predictive Control for Towing Kites - A Question of Formulation or Learning?
2023 IEEE Conference on Control Technology and Applications. Bridgetown, Barbados (16.-18.08.2023)
doi: 10.1109/CCTA54093.2023.10252231
Conference or Workshop Item, Bibliographie
Abstract
Towing kites bear large potential for carbon neutral energy generation using high altitude wind. However, to realize this potential reliable, safe, and efficient control is essential. This task is often tackled using a trajectory tracking model predictive control formulation. We show that such a formulation limits the achievable performance due to a fixed and predefined trajectory speed. This can be bypassed by a tailored path following predictive control formulation, enhancing the controller’s robustness in different scenarios. Additionally, we show that learning an accurate model using input-output data improves the performance of both path following and trajectory tracking. In case of the trajectory tracking controller the improvements allow to mask its inherent drawbacks, raising the question whether learning can be used to compensate an unfavorable problem formulation. Our results show that the path following controller performs well for a wide range of parameters and exhibits a trade-off between generated thrust and tracking accuracy. Furthermore, the path following controller significantly outperforms the trajectory tracking controller in terms of robustness.
| Item Type: | Conference or Workshop Item |
|---|---|
| Erschienen: | 2023 |
| Creators: | Höhl, Andreas ; Maiworm, Michael ; Findeisen, Rolf |
| Type of entry: | Bibliographie |
| Title: | Path Following or Tracking Model Predictive Control for Towing Kites - A Question of Formulation or Learning? |
| Language: | English |
| Date: | 22 September 2023 |
| Place of Publication: | Bridgetown, Barbados |
| Publisher: | IEEE |
| Book Title: | 2023 IEEE Conference on Control Technology and Applications (CCTA) |
| Event Title: | 2023 IEEE Conference on Control Technology and Applications |
| Event Location: | Bridgetown, Barbados |
| Event Dates: | 16.-18.08.2023 |
| DOI: | 10.1109/CCTA54093.2023.10252231 |
| Abstract: | Towing kites bear large potential for carbon neutral energy generation using high altitude wind. However, to realize this potential reliable, safe, and efficient control is essential. This task is often tackled using a trajectory tracking model predictive control formulation. We show that such a formulation limits the achievable performance due to a fixed and predefined trajectory speed. This can be bypassed by a tailored path following predictive control formulation, enhancing the controller’s robustness in different scenarios. Additionally, we show that learning an accurate model using input-output data improves the performance of both path following and trajectory tracking. In case of the trajectory tracking controller the improvements allow to mask its inherent drawbacks, raising the question whether learning can be used to compensate an unfavorable problem formulation. Our results show that the path following controller performs well for a wide range of parameters and exhibits a trade-off between generated thrust and tracking accuracy. Furthermore, the path following controller significantly outperforms the trajectory tracking controller in terms of robustness. |
| Divisions: | 18 Department of Electrical Engineering and Information Technology 18 Department of Electrical Engineering and Information Technology > Institut für Automatisierungstechnik und Mechatronik 18 Department of Electrical Engineering and Information Technology > Institut für Automatisierungstechnik und Mechatronik > Control and Cyber-Physical Systems (CCPS) |
| Date Deposited: | 19 Oct 2023 10:11 |
| Last Modified: | 31 Oct 2023 07:19 |
| PPN: | 512781796 |
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