The landing on carrier is a very difficult task even for trained pilots. This paper presents a method to land automatically using aircraft sensors and three visual features inspired by visual cues used by pilots. These features whose link with the aircraft state is established, are introduced in a control scheme using a linearized aircraft model. The control law demonstrates a large convergence domain using simulated visual features and a 3D tracker applied on synthetic images.

This paper describes a control strategy to stabilize the position of a vertical takeoff and landing (VTOL) unmanned aerial vehicle (UAV) in wind gusts. The proposed approach takes advantage of the cascade structure of the system to design a hierarchical controller. The idea is to separate the controller in a high level controller devoted to position control and a low level controller devoted to stabilization and attitude control. Both controllers are designed by means of backstepping techniques that allow the stabilization of the vehicle's position while on-line estimation of the unknown aerodynamic forces. The global stability of the connected system is proven, and simulations as well as experimental results are presented

This paper deals with the autonomous navigation of a ducted fan vertical take off and landing (VTOL) unmanned aerial vehicle (UAV) in constrained environment. The proposed strategy considers the translational dynamics of the vehicle to design a control of the thrust vector that ensures safe navigation in presence of encountered obstacles. Adaptive backstepping techniques are used to design a nonlinear feedback control that allows to navigate amidst obstacles despite wind perturbations. Simulations results and a first experiment are presented to illustrate the concept

In this paper, a nonlinear complimentary filter (x-estimator) is presented to estimate the attitude of a UAV (unmanned aerial vehicle). The measurements are taken from a low-cost SMU (inertial measurement unit) which consists of 3-axis accelerometers and 3-axis gyroscopes. The gyro bias are estimated online. A second nonlinear complimentary filter (z-estimator) is also designed, it combines 3-axis gyroscope readings with 3-axis magnetometer measurements. From the proposed estimators, the full rotation matrix R will be retrieved. Both estimators use the fact that the orientation matrix, evolving on SO(3), is not locally parameterized and thus could be used to describe any kind of 3D motion. Convergence of the two observers is theoretically proved and simulations as well as experiments are conducted on a real platform in hovering flight conditions.