The estimation of the Angle of Attack (AOA) and Angle of Sideslip (AOS) is crucial for flight monitoring and control. However, a gap has been identified on the data selection technique for the class of estimators based on data-driven methods, such as the synthetic sensor based on Neural Network (NN). This paper proposes a Cross Validation (CV) technique applied on a manoeuver-based partitioning method to provide evidence that a given selection of data can lead to better estimation performance, with the final aim of providing a list of manoeuvers suitable for the training phase of the estimator. Results are shown using simulated data related to the CleanSky 2 project MIDAS.
Maneuver-Based Cross-Validation Approach for Angle-of-Attack Estimation / Brandl, A.; Battipede, M.. - ELETTRONICO. - 1(2021), pp. 1-10. ((Intervento presentato al convegno 14th World Congress on Computational Mechanics (WCCM) ECCOMAS Congress 2020 tenutosi a Virtual Congress nel 11-15 January 2021.
Titolo: | Maneuver-Based Cross-Validation Approach for Angle-of-Attack Estimation | |
Autori: | ||
Data di pubblicazione: | 2021 | |
Abstract: | The estimation of the Angle of Attack (AOA) and Angle of Sideslip (AOS) is crucial for flight mo...nitoring and control. However, a gap has been identified on the data selection technique for the class of estimators based on data-driven methods, such as the synthetic sensor based on Neural Network (NN). This paper proposes a Cross Validation (CV) technique applied on a manoeuver-based partitioning method to provide evidence that a given selection of data can lead to better estimation performance, with the final aim of providing a list of manoeuvers suitable for the training phase of the estimator. Results are shown using simulated data related to the CleanSky 2 project MIDAS. | |
Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
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http://hdl.handle.net/11583/2876752