Steven Aurecianus

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.

A hover-capable insect-inspired flying robot that can remain long in the air has shown its potential use for both confined indoor and outdoor applications to complete assigned tasks. In this letter, we report improvements in the flight endurance of our 15.8 g robot, named KUBeetle-S, using a low-voltage power source. The robot is equipped with a simple but effective control mechanism that can modulate the stroke plane for attitude stabilization and control. Due to the demand for extended flight, we performed a series of experiments on the lift generation and power requirement of the robot with different stroke amplitudes and wing areas. We show that a larger wing with less inboard wing area improves the lift-to-power ratio and produces a peak lift-to-weight ratio of 1.34 at 3.7 V application. Flight tests show that the robot employing the selected wing could hover for 8.8 minutes. Moreover, the robot could perform maneuvers in any direction, fly outdoors, and carry payload, demonstrating its ability to enter the next phase of autonomous flight.

In this study, the stable proportional–derivative (PD) controller gains for pitch control (longitudinal control) are obtained using the linearized and non-coupled longitudinal-mode flight dynamics model of the tailless, hover-capable, flapping wing robot named KUBeetle. To acquire a more realistic longitudinal model of KUBeetle, we incorporated the dynamics of the sensors, filters, and servo. Then, the range of PD controller gains that yield stable and sufficient stability robustness are determined using the Routh–Hurwitz, root locus, and H_∞ norm stability analyses. We observed that the stability of the closed loop controller is affected significantly by the dynamics that are incorporated. The PD controller gain with good robustness is selected based on the stability analysis. However, the low frequency gain of the PD controller was too small to attain the setpoint, although the stability margin was sufficiently high. A loop shaping compensator is designed and added to the control loop to improve the low frequency gain while sustaining the stability margin. The frequency and time domain analyses reveal that the proposed control loop can be used for stabilizing KUBeetle. To test the performance experimentally, we implemented the control loop in an onboard control system, which includes a microprocessor and MEMS sensors. The experimental results closely matched the simulation results, demonstrating that the proposed controller could maintain stability in a real system with high flapping noises.