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http://dx.doi.org/10.12989/aas.2021.8.4.273

Physics-based modelling for a closed form solution for flow angle estimation  

Lerro, Angelo (Department of Mechanical and Aerospace Engineering, Polytechnic University of Turin)
Publication Information
Advances in aircraft and spacecraft science / v.8, no.4, 2021 , pp. 273-287 More about this Journal
Abstract
Model-based, data-driven and physics-based approaches represent the state-of-the-art techniques to estimate the aircraft flow angles, angle-of-attack and angle-of-sideslip, in avionics. Thanks to sensor fusion techniques, a synthetic sensor is able to provide estimation of flow angles without any dedicated physical sensors. The work deals with a physics-based scheme derived from flight mechanic theory that leads to a nonlinear flow angle model. Even though several solvers can be adopted, nonlinear models can be replaced with less accurate but straightforward ones in practical applications. The present work proposes a linearisation to obtain the flow angles' closed form solution that is verified using a flight simulator. The main objective of the paper, in fact, is to analyse the estimation degradation using the proposed closed form solutions with respect to the nonlinear scheme. Moreover, flight conditions, where the proposed closed form solutions are not applicable, are identified.
Keywords
flow angles; flight mechanics; model-free;
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1 Fravolini, M.L., Del Core, G., Papa, U., Valigi, P. and Napolitano, M.R. (2019), "Data-Driven Schemes for Robust Fault Detection of Air Data System Sensors", IEEE Transactions on Control Systems Technology, 27(1), 234-248.   DOI
2 Salychev, O.S. (2004), Applied Inertial Navigation: Problems and Solutions, BMSTU Press.
3 Colgren, R., Frye, M. and Olson, W. (1999), "A proposed system architecture for estimation of angle-of-attack and sideslip angle", in "Guidance, Navigation, and Control Conference and Exhibit", c, pages 743-750, American Institute of Aeronautics and Astronautics, Reston, Virigina, URL http://arc.aiaa.org/doi/10.2514/6.1999-4078.
4 Dendy, J. and Transier, K. (1969), Angle-of-Attack Computation Study, Technical report, Air Force Flight Dynamics Laboratory, aFFDL-TR-69-93.
5 Etkin, B. and Reid, L. (1995), Dynamics of Flight: Stability and Control; Third Edition, Wiley.
6 Eubank, R., Atkins, E. and Ogura, S. (2010), "Fault Detection and Fail-Safe Operation with a Multiple-Redundancy Air-Data System", in "AIAA Guidance, Navigation, and Control Conference", August 2010, pages 1-14, American Institute of Aeronautics and Astronautics, Reston, Virigina, URL http://arc.aiaa.org/doi/10.2514/6.2010-7855.
7 Freeman, D.B. (1973), Angle of Attack Computation System, Technical report, Air Force Flight Dynamics Laboratory, aFFDL-TR-73-89.
8 Gavrilovic, N., Bronz, M., Moschetta, J.M. and Benard, E. (2018), "Bioinspired wind field estimation-part 1: Angle of attack measurements through surface pressure distribution", International Journal of Micro Air Vehicles, 10(3), 273-284, URL https://doi.org/10.1177/1756829318794172, https://doi.org/10.1177/1756829318794172.   DOI
9 Lerro, A., Brandl, A. and Gili, P. (2021), "Model-Free Scheme for Angle-of-Attack and Angle-of-Sideslip Estimation", Journal of Guidance, Control, and Dynamics, 44(3), 595-600.   DOI
10 Nelson, R. (1989), Flight stability and automatic control, McGraw-Hill series in aeronautical and aerospace engineering, McGraw-Hill Ryerson, Limited.
11 Lu, P., van Kampen, E.J., de Visser, C. and Chu, Q. (2020), "Air Data Sensor Fault Detection and Diagnosis in the Presence of Atmospheric Turbulence: Theory and Experimental Validation With Real Flight Data", IEEE Transactions on Control Systems Technology, pages 1-9.
12 Popowski, S. and Dabrowski, W. (2015), "Measurement and estimation of the angle of attack and the angle of sideslip", Aviation, 19(1), 19-24.   DOI
13 Schmidt, D. (2011), Modern Flight Dynamics, ASIA HIGHER EDUCATION ENGINEER, McGraw-Hill, URL https://books.google.it/books?id=TofEXwAACAAJ.
14 Tian, P., Chao, H., Rhudy, M., Gross, J. and Wu, H. (2021), "Wind Sensing and Estimation Using Small Fixed-Wing Unmanned Aerial Vehicles: A Survey", Journal of Aerospace Information Systems, 18(3), 132-143, URL https://doi.org/10.2514/1.I010885, https://doi.org/10.2514/1.I010885.   DOI
15 Marzat, J., Piet-Lahanier, H., Damongeot, F. and Walter, E. (2012), "Model-based fault diagnosis for aerospace systems: a survey", Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 226(10), 1329-1360, URL https://doi.org/10.1177/0954410011421717, https://doi.org/10.1177/0954410011421717.   DOI
16 Pouliezos, A.D. and Stavrakakis, G.S. (1994), "Analytical Redundancy Methods", in "Real Time Fault Monitoring of Industrial Processes", volume 12, pages 93-178, Springer Netherlands, Dordrecht, URL https://doi.org/10.1007/978-94-015-8300-8 2.   DOI
17 Sun, K., Regan, C.D. and Egziabher, D.G. (2018), "GNSS/INS based estimation of air data and wind vector using flight maneuvers", in "2018 IEEE/ION Position, Location and Navigation Symposium (PLANS)", pages 838-849, IEEE, URL https://ieeexplore.ieee.org/document/8373461/.