Wind disturbance compensated path-following control for fixed-wing UAVs in arbitrarily strong winds

Wind is the primary challenge for low-speed fixed-wing unmanned aerial vehicles to follow a predefined flight path.To cope with various wind conditions,this paper proposes a wind disturbance compensated path following control strategy where the wind disturbance estimate is incorporated with the nominal guiding vector field to provide the desired airspeed direction for the inner-loop.Since the control input vector for the outer-loop kinematic subsystem needs to satisfy a magnitude constraint,a scaling mechanism is introduced to tune the proportions of the compensation and nominal components.Moreover,an optimization problem is formulated to pursue a maximum wind compensation in strong winds,which can be solved analytically to yield two scaling factors.A cascaded inner-loop tracking controller is also designed to fulfill the outer-loop wind disturbance compensated guiding vector field.High-fidelity simulation results under sensor noises and realistic winds demonstrate that the proposed path following algorithm is less sensitive to sensor noises,achieves promising accuracy in normal winds,and mitigates the deviation from a desired path in wild winds.

Energy-efficiency maximization for fixed-wing UAV-enabled relay network with circular trajectory

With the development of Unmanned Aerial Vehicles(UAVs), the applications of UAVs have been extensively explored. In the field of wireless communications, the relay nodes are often used to extend network coverage. However, traditional fixed ground relays cannot be flexibly deployed due to their low heights and fixed locations. Hence, deploying UAV as relay node is a promising solution and has become a research hotspot. In this paper, we consider an UAVenabled relaying network in which a fixed-wing UAV is deployed between the Base Station(BS)and Ground Users(GUs). We study the energy-efficiency gap between the link “BS-UAV-GUs”and the link “BS-GUs”, and jointly optimize UAV relay transmission power and flight radius to achieve the highest energy-efficiency. Firstly, the UAV/BS-GUs channels models and the UAV energy consumption model are built. Secondly, the optimization objective function is formulated to maximize the energy-efficiency gap. Then, the solution of the optimization problem is divided into a two-step iteration process, in which the UAV relay transmission power and flight radius are adjusted to maximize the energy-efficiency gap. Finally, the experimental results under different simulation scenarios(such as cities, forests, deserts, oceans, etc.) are shown to illustrate the effectiveness of the proposed algorithm. The results show that the proposed algorithm can always find the optimal UAV relay transmission power and flight radius settings, and achieve the largest energy-efficiency gap. The convergency speed of the proposed algorithm is fast, and can obtain the optimal solution within only a few iterations.