This paper presents an aeromechanics investigation of tiltrotor aircraft through the conversion regime of flight. The effects of the rotors-on-wing, rotors-on-empennage and wing-on-empennage interactions were investigated singularly and collectively to assess their impacts on trim behaviour, performance and conversion boundaries. The rotors-on-wing download was found to be dominant in the prediction of hover and low-speed flight performance and had a degrading effect overall. The fuselage pitch attitude and stick position were found to be significantly affected by the empennage interaction cases throughout the conversion domain. The large flap/flaperon settings used to alleviate the rotor download contributed considerably to the low-speed trim behaviour. The conversion boundaries were found to be insensitive to all the interaction cases, though the min-speed boundary was reduced marginally due to the wing-on-empennage interaction. The results showed that the combined interactions were important factors to accurately predict the trim behaviour and aircraft performance throughout the conversion corridor.

Backstepping represents a promising control law for fixed-wing Unmanned Aerial Vehicles (UAVs). Its non-linearity and its adaptation capabilities guarantee adequate control performance over the whole flight envelope, even when the aircraft model is affected by parametric uncertainties. In the literature, several works apply backstepping controllers to various aspects of fixed-wing UAV flight. Unfortunately, many of them have not been implemented in a real-time controller, and only few attempt simultaneous longitudinal and lateral–directional aircraft control. In this paper, an existing backstepping approach able to control longitudinal and lateral–directional motions is adapted for the definition of a control strategy suitable for small UAV autopilots. Rapidly changing inner-loop variables are controlled with non-adaptive backstepping, while slower outer loop navigation variables are Proportional–Integral–Derivative (PID) controlled. The controller is evaluated through numerical simulations for two very diverse fixed-wing aircraft performing complex manoeuvres. The controller behaviour with model parametric uncertainties or in presence of noise is also tested. The performance results of a real-time implementation on a microcontroller are evaluated through hardware-in-the-loop simulation.

Large birds have evolved an effective wing anatomy and mechanics, enabling airborne mastery of manoeuvres and endurance. For these very reasons, they are difficult to replicate and study. The aim of the present work is to achieve active wing articulations to mimic natural bird flapping towards efficient and agile Unmanned Aerial Vehicles (UAVs). The proposed design, bio-mimicking the black-headed gull, Larus ridibundus, has three active and independent servo-controlled wing joints at the shoulder, elbow and wrist to achieve complex controls. The construction of the wing is realised through a polymeric skin and carbon fibre–epoxy composite spars and ribs. The wing movements (flapping, span reduction and twisting) envelopes of the full-scale robotic gull (Robogull) are examined using the Digital Image Correlation (DIC) technique and laser displacement sensing. Its aerodynamic performance was evaluated in a wind tunnel at various flapping parameters, wind speeds and angles of attack. It is observed that a flapping amplitude of 45 $^\circ$ is more favourable than 90 $^\circ$ for generating higher lift and thrust, while also depending on the presence of span reduction, twist and wind speed. The model performs better at a flying velocity of 4m/s as compared with 8m/s. Both lift and thrust are high at a higher flapping frequency of 2.5Hz. Combined variation of the flapping frequency and stroke ratio should be considered for better aerodynamic performance. The combination of a lower stroke ratio of 0.5 with a flapping frequency of 2.5Hz generates higher lift and thrust than other combinations. Span reduction and wing twist notably and independently enhance lift and thrust, respectively. An increase in the angle-of-attack increases lift but decreases thrust. The model can also generate a significant rolling moment when set at a bank angle of 20 $^\circ$ and operated with independently controlled flapping amplitudes for the wings (45 $^\circ$ for the left wing and 90 $^\circ$ for the right wing). Based on the optimal values for the flapping amplitude (45 $^\circ$ ), flapping frequency (2.5Hz) and flying velocity (4m/s), the Strouhal number (St) of the Robogull model is 0.24, lying in the optimal range ( $0.2 < \mathrm{St} < 0.4$ ) for natural flyers and swimmers.

To improve the ability of avian radar to process bird information, a statistical analysis method for the bird situation around airport is proposed based on avian radar data. By accumulating a large amount of avian radar data, hotspots of the activity area of bird targets can be determined and taken as a reference point to realise lifecycle management of each bird target from initiation to continuation and finally death. In the process of target tracking, combined with the particle filter method, the probability of several possible events is estimated, leading to completion of the data association and real-time statistics for the number of targets. The simulation results reveal that this method is superior to the traditional logic method regarding the timeliness of multi-target initiation. With the application of the proposed method to avian radar data, the bird population and its basic activity rules can be discovered by fixing the bird habitats around the airport.

Recently, transformable Unmanned Aerial Vehicles (UAVs) have become a subject of great interest in the field of flying systems, due to their maneuverability, agility and morphological capacities. They can be used for specific missions and in more congested spaces. Moreover, this novel class of UAVs is considered as a viable solution for providing flying robots with specific and versatile functionalities. In this paper, we propose (i) a new design of a transformable quadrotor with (ii) generic modeling and (iii) adaptive control strategy. The proposed UAV is able to change its flight configuration by rotating its four arms independently around a central body, thanks to its adaptive geometry. To simplify and lighten the prototype, a simple mechanism with a light mechanical structure is proposed. Since the Center of Gravity (CoG) of the UAV moves according to the desired morphology of the system, a variation of the inertia and the allocation matrix occurs instantly. These dynamics parameters play an important role in the system control and its stability, representing a key difference compared with the classic quadrotor. Thus, a new generic model is developed, taking into account all these variations together with aerodynamic effects. To validate this model and ensure the stability of the designed UAV, an adaptive backstepping control strategy based on the change in the flight configuration is applied. MATLAB simulations are provided to evaluate and illustrate the performance and efficiency of the proposed controller. Finally, some experimental tests are presented.

The capability of aircraft tyres to sustain landing impact loads is essential for flight landing safety. Hence, the development of a reliable experimental database is necessary to validate numerical models. The experimental data on aircraft tyre landing impact in the public literature are somewhat sparse. This paper describes a detailed design rig for aircraft tyre impact testing. A finite element model is then created and simulated using a finite element tool (ABAQUS). Inflation and static load simulations are analysed based on the FE tyre model to confirm its reliability. Comparison of experimental measurements with the results reveals that the model can predict the significant features of aircraft tyre impact in a landing scenario. Very little experimental data are publicly available to verify aircraft tyre models. Therefore, the experimental data in this paper fill this gap in the literature.

This paper aims to accurately estimate the lateral directional aerodynamic parameters in real time irrespective of the variations in the process and measurement covariance matrices. The proposed algorithm for parameter estimation is based on the integration of adaptive techniques into a stochastic nonlinear filter. The proposed adaptive estimation algorithm is applied to flight test data, and the lateral directional derivatives are estimated in real time. The estimates are compared with those obtained from the Filter Error Method (FEM), an offline parameter estimation method accounting for process noise. The estimation results are observed to be very comparable, and the supremacy of the adaptive filter is illustrated by varying the covariance matrices of both process and measurement noises. The parameters estimated by the adaptive filter are found to converge to their actual values, whereas the estimates of the regular filter are observed to diverge from the actual values when changing the noise covariance matrices. The proposed adaptive algorithm can estimate the lateral directional aerodynamic derivatives more accurately without prior knowledge of either process or measurement noise covariance matrices. Hence, it is of great value in online implementations.