<p>This paper presents an experimental study on developing and validating a simulation-ready aerodynamic model for the Skywalker X8 unmanned aerial vehicle (UAV) using a hybrid output error method (OEM). Building on previous efforts, we introduce an updated 6-degree-of-freedom (DOF) nonlinear aerodynamic model and its linearized form. The key features of this work include the model’s identification in the stability frame, achieved using estimated angle of attack and sideslip angle, and the use of a propulsion system model to obtained the motor speed data. The stability frame parameterization allows for direct comparisons with a larger set of UAV models and computational fluid dynamics (CFD) results, often presented in terms of lift and drag analysis. Key advancements include a residual distribution analysis that was successfully applied to identify and correct weaknesses in the initial drag and side force models. Additionally, the paper addresses the unique combination of challenges faced during this study and describes strategies for managing strong winds during experiments, use of a propulsion system model to obtain motor speed data, and utilization of estimated aerodynamic angles. The resulting model is validated against a separate set of maneuvers comprising 10-s-long sequences that include estimated body states, force and moment coefficients, and estimated air data states, (<InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="13272_2025_816_Article_IEq1.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="19" /> </InlineMediaObject> <EquationSource Format="TEX">$V_a$</EquationSource> <EquationSource Format="MATHML"><math> <msub> <mi>V</mi> <mi>a</mi> </msub> </math></EquationSource> </InlineEquation>, <InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="13272_2025_816_Article_IEq2.gif" Format="GIF" Height="10" Rendition="HTML" Resolution="72" Type="Linedraw" Width="14" /> </InlineMediaObject> <EquationSource Format="TEX">$\alpha$</EquationSource> <EquationSource Format="MATHML"><math> <mi>α</mi> </math></EquationSource> </InlineEquation>, <InlineEquation ID="IEq3"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="13272_2025_816_Article_IEq3.gif" Format="GIF" Height="17" Rendition="HTML" Resolution="72" Type="Linedraw" Width="15" /> </InlineMediaObject> <EquationSource Format="TEX">$\beta$</EquationSource> <EquationSource Format="MATHML"><math> <mi>β</mi> </math></EquationSource> </InlineEquation>), for both lateral and longitudinal maneuvers.</p>

Modeling and identification of a small fixed-wing UAV using estimated aerodynamic angles

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2025年2月26日

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Bogdan Løw-Hansen,
Richard Hann,
Kristoffer Gryte,
Tor Arne Johansen,
Christoph Deiler

摘要

This paper presents an experimental study on developing and validating a simulation-ready aerodynamic model for the Skywalker X8 unmanned aerial vehicle (UAV) using a hybrid output error method (OEM). Building on previous efforts, we introduce an updated 6-degree-of-freedom (DOF) nonlinear aerodynamic model and its linearized form. The key features of this work include the model’s identification in the stability frame, achieved using estimated angle of attack and sideslip angle, and the use of a propulsion system model to obtained the motor speed data. The stability frame parameterization allows for direct comparisons with a larger set of UAV models and computational fluid dynamics (CFD) results, often presented in terms of lift and drag analysis. Key advancements include a residual distribution analysis that was successfully applied to identify and correct weaknesses in the initial drag and side force models. Additionally, the paper addresses the unique combination of challenges faced during this study and describes strategies for managing strong winds during experiments, use of a propulsion system model to obtain motor speed data, and utilization of estimated aerodynamic angles. The resulting model is validated against a separate set of maneuvers comprising 10-s-long sequences that include estimated body states, force and moment coefficients, and estimated air data states, ( $V_a$ $V_{a}$ , $\alpha$ $α$ , $\beta$ $β$ ), for both lateral and longitudinal maneuvers.