In this paper, model parameter identification results are presented for a longitudinal mode dynamic model of an insect-like tailless flapping-wing micro air vehicle (FWMAV) using angle and angular rate data from onboard sensors only. A gray box model approach with indirect method was utilized with adaptive Gauss–Newton, Levenberg–Marquardt, and gradient search identification methods. Regular and low-frequency reference commands were mainly used for identification since they gave higher fit percentages than irregular and high-frequency reference commands. Dynamic parameters obtained using three identification methods with two different datasets were similar to each other, indicating that the obtained dynamic model was sufficiently reliable. Most of the identified dynamic model parameters had similar values to the computationally obtained ones, except stability derivatives for pitching moment with forward velocity and pitching rate variations. Differences were mainly due to certain neglected body, nonlinear dynamics, and the shift of the center of gravity. Fit percentage of the identified dynamic model (~49%) was more than two-fold higher than that of the computationally obtained one (~22%). Frequency domain analysis showed that the identified model was much different from that of the computationally obtained one in the frequency range of 0.3 rad/s to 5 rad/s, which affected transient responses. Both dynamic models showed that the phase margin was very low, and that it should be increased by a feedback controller to have a robustly stable system. The stable dominant pole of the identified model had a higher magnitude which resulted in faster responses. The identified dynamic model exhibited much closer responses to experimental flight data in pitching motion than the computationally obtained dynamic model, demonstrating that the identified dynamic model could be used for the design of more effective pitch angle-stabilizing controllers.

The ability to predict lift is crucial for enabling flapping flights on planets with varying air densities and gravities. After determining the lift required for a flapping flight on Earth, it can be predicted under different conditions using a scaling equation as a function of air density and gravity, assuming the cycle-average lift coefficient remains constant. However, in flapping wings, passive deformation due to aerodynamic and inertial forces may alter the flapping-wing kinematics, complicating predictions. In this study, we investigated changes in the lift coefficient of flapping wings under various air density and gravity conditions simulated using a low-pressure chamber and tilting stand, respectively. The current study found that the cycle-averaged lift coefficients remained nearly constant, varying by less than 7% across the air density and gravity conditions. The difference between the measured and predicted hovering frequencies increased under a lower air density due to the higher vibration-induced friction. The power consumption analysis demonstrated higher energy demands in thinner atmospheres and predicted a required power of 5.14 W for a hovering flight on Mars, which is a 66% increase compared to that on Earth. Future experiments will test Martian air density and gravity conditions to enable flapping flights on Mars.