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Flying animals resort to fast, large-degree-of-freedom motion of flappingwings, a key feature that distinguishes them from rotary or fixed-wingedrobotic fliers with limited motion of aerodynamic surfaces. However,flapping-wing aerodynamics are characterised by highly unsteady andthree-dimensional flows difficult to model or control, and accurate aerodynamicforce predictions often rely on expensive computational or experimentalmethods. Here, we developed a computationally efficient and data-drivenstate-space model to dynamically map wing kinematics to aerodynamicforces/moments. This model was trained and tested with a total of 548 differentflapping-wing motions and surpassed the accuracy and generality of the existingquasi-steady models. This model used 12 states to capture the unsteady andnonlinear fluid effects pertinent to force generation without explicitinformation of fluid flows. We also provided a comprehensive assessment of thecontrol authority of key wing kinematic variables and found that instantaneousaerodynamic forces/moments were largely predictable by the wing motion historywithin a half-stroke cycle. Furthermore, the angle of attack, normalacceleration, and pitching motion had the strongest effects on the aerodynamicforce/moment generation. Our results show that flapping flight inherentlyoffers high force control authority and predictability, which can be key todeveloping agile and stable aerial fliers.

State-space aerodynamic model reveals high force control authority and predictability in flapping flight