An accurate knowledge of the unsteady aerodynamic forces acting on a bio-inspired, flapping-wing micro air vehicle (FWMAV) is crucial in the design development and optimization cycle. Two different types of experimental approaches are often used: determination of forces from position data obtained from external optical tracking during free flight, or direct measurements of forces by attaching the FWMAV to a force transducer in a wind-tunnel. This study compares the quality of the forces obtained from both methods as applied to a 17.4 gram FWMAV capable of controlled flight. A comprehensive analysis of various error sources is performed. The effects of different factors, e.g., measurement errors, error propagation, numerical differentiation, filtering frequency selection, and structural eigenmode interference, are assessed. For the forces obtained from free flight experiments it is shown that a data acquisition frequency below 200 Hz and an accuracy in the position measurements lower than ± 0.2 mm may considerably hinder determination of the unsteady forces. In general, the force component parallel to the fuselage determined by the two methods compares well for identical flight conditions; however, a significant difference was observed for the forces along the stroke plane of the wings. This was found to originate from the restrictions applied by the clamp to the dynamic oscillations observed in free flight and from the structural resonance of the clamped FWMAV structure, which generates loads that cannot be distinguished from the external forces. Furthermore, the clamping position was found to have a pronounced influence on the eigenmodes of the structure, and this effect should be taken into account for accurate force measurements.
This paper presents an approach to the system identification of the Delfly II Flapping Wing Micro Air Vehicle (FWMAV) using flight test data. It aims at providing simple FWMAV aerodynamic models that can be used in simulations as well as in nonlinear flight control systems. The undertaken methodology builds on normal aircraft system identification methods and extends these with techniques that are specific to FWMAV model identification. The entire aircraft model identification cycle is discussed covering the set-up and automatic execution of the flight test experiments, the aircraft states, the aerodynamic forces and moments' reconstruction, the aerodynamic model structure selection, the parameter estimation and finally, the model validation. In particular, a motion capturing facility was used to record the flapper's position in time and from there compute the states and aerodynamic forces and moments that acted on it, assuming flapaveraged dynamics and linear aerodynamic model structures. It is shown that the approach leads to aerodynamic models that can predict the aerodynamic forces with high accuracy. Despite less accurate, the predictions of the aerodynamic moments still follow the general trend of the measured moments. Dynamic simulations based on the identified aerodynamic models show flight trajectories that closely match the ground truth spanning a number of flapping cycles. Finally, the dimensional aerodynamic forces and moments' coefficients of two of the identified aerodynamic models are presented.
Flapping-wing aerodynamic models that are accurate, computationally efficient and physically meaningful, are challenging to obtain. Such models are essential to design flapping-wing micro air vehicles and to develop advanced controllers enhancing the autonomy of such vehicles. In this work, a phenomenological model is developed for the time-resolved aerodynamic forces on clap-and-fling ornithopters. The model is based on quasi-steady theory and accounts for inertial, circulatory, added mass and viscous forces. It extends existing quasi-steady approaches by: including a fling circulation factor to account for unsteady wing-wing interaction, considering real platform-specific wing kinematics and different flight regimes. The model parameters are estimated from wind tunnel measurements conducted on a real test platform. Comparison to wind tunnel data shows that the model predicts the lift forces on the test platform accurately, and accounts for wing-wing interaction effectively. Additionally, validation tests with real free-flight data show that lift forces can be predicted with considerable accuracy in different flight regimes. The complete parameter-varying model represents a wide range of flight conditions, is computationally simple, physically meaningful and requires few measurements. It is therefore potentially useful for both control design and preliminary conceptual studies for developing new platforms.
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