Using Broadcast Wind Observations to Update the Optimal Descent Trajectory in Real-Time
The ability to meet a controlled time of arrival during a continuous descent operation will enable environmentally friendly and fuel-efficient descent operations while simultaneously maintaining airport throughput. However, if the wind forecast used to compute the initial trajectory plan is not accu...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2020 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/183440 |
| Acceso en línea: | https://hdl.handle.net/2117/183440 https://dx.doi.org/10.2514/1.D0174 |
| Access Level: | acceso abierto |
| Palabra clave: | Wind forecasting Airplanes -- Performances Trajectory optimization Airplanes Meteorology Wind networking NMPC ADS-B CDO CTA Optimització de trajectòria Avions Meteorologia Àrees temàtiques de la UPC::Aeronàutica i espai |
| Sumario: | The ability to meet a controlled time of arrival during a continuous descent operation will enable environmentally friendly and fuel-efficient descent operations while simultaneously maintaining airport throughput. However, if the wind forecast used to compute the initial trajectory plan is not accurate enough, the guidance system will need to correct time deviations from the plan during the execution of the descent. Previous work proposed an onboard guidance strategy based on model predictive control, which repeatedly updates the trajectory plan in real-time from the current aircraft state and for the remainder of the descent. However, the wind conditions downstream, at altitudes not explored yet, were difficult to predict due to the lack of data. This paper shows the potential benefits of using wind observations, broadcast by nearby aircraft, to reconstruct the wind profile downstream. The wind profile in the trajectory optimization problem is modeled as a spline, control points of which are updated to fit the observations before replanning the trajectory. Results from simulations using realistic wind data show that the performance of model predictive control significantly improves when including up-to-date wind observations, in terms of time and energy errors at the metering fix and fuel consumption. |
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