This paper analyzes the lift-production system in hovering of the flapping wing robot COLIBRI of the size of a hummingbird. The paper first examines the flapping wing mechanism for which a new gear transmission is proposed to reduce the friction and facilitate the assembly. Next, a sensitivity analysis is performed on the wing size. Then, the paper discusses several options for the gearbox, various DC motors and two battery configurations (a single battery or two batteries in series) to minimize the heat generation and increase the flight time. The configuration involving two batteries has been found more effective. The flight time is predicted using Shepherd’s discharge model and it is confirmed by an experiment. The robot sustains an endurance of nearly 5 min to produce a lift force equal to the weight of the robot.

Aiming at the vibrations of the multistage gear transmission system aroused by the gear meshing excitation, a novel active vibration control structure with built‐in piezoelectric actuators (PZT) was established. The active control forces generated by the PZT were transmitted to the shafts through the additional supporting bearings. In addition, an adaptive fuzzy proportion integration differentiation (AFPID) control algorithm was proposed as the primary control algorithm to reduce the transverse vibrations of the gear shaft. According to the control law of PID parameters, a fuzzy inference module was designed to adaptively adjust the PID parameters to obtain the optimal control effect. An experimental platform was set up to verify the control effect of the algorithm. The experiments performed show 10 dB reduction in housing vibrations at certain targeted mesh harmonics over a range of operating speeds.

The paper reports on flight tests at hovering of the COLIBRI robot. After a short review of the control model and the stabilization strategy, two different approaches are considered for the attitude reconstruction from the MEMS Inertial Measurement Unit (IMU): the complementary filter and the full-state dynamic observer, implemented in a specially designed flight control board. It is shown that both strategies provide adequate stabilization at hovering in spite of the strong vibration excitation resulting from the flapping of the wings. Moreover, it is shown that the residual wandering due to noise, robot imperfection, etc., can be significantly reduced by a cascade control loop based on the axial and lateral velocities reconstructed by the full-state observer. Experiments show that this approach based on onboard measurements allows for a station keeping as good as that obtained with velocities reconstructed from an external tracking system. The paper also reports endurance tests conducted with two different robot configurations; the maximum flight time observed is 4 min 30 s.

After a short overview of the COLIBRI project, this paper considers the cycle-averaged flight dynamics of a flapping-wing robot near hovering, taking advantage of the weak coupling between the roll and pitch axes. The system is naturally unstable; it needs to be stabilized actively, which requires an attitude reconstruction. Due to the flapping of the wings, the system is subject to a strong periodic noise at the flapping frequency and its higher harmonics; the resulting axial forces and pitch moments are characterized from experimental data. The flapping noise propagates to the six-axis Inertial Measurement Unit (IMU) consisting of three accelerometers and three gyros. The paper is devoted to attitude reconstruction in the presence of flapping noise representative of flight conditions. Two methods are considered: (i) the complementary filter based on the hovering assumption and (ii) a full-state dynamic observer (Kalman filter). Unlike the complementary filter, the full-state dynamic observer allows the reconstruction of the axial velocity, allowing us to control the hovering without any additional sensor. A numerical simulation is conducted to assess the merit of the two methods using experimental noise data obtained with the COLIBRI robot. The paper discusses the trade-off between noise rejection and stability.