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Abstract In a probe–drogue aerial refueling system, the drogue is affected not only by wind disturbances but also by strong disturbances from the tanker vortex and receiver forebody bow wave. Along with the aerodynamic disturbances acting on the receiver aircraft, it is difficult for the probe to capture the moving drogue in the docking stage. This paper studies the model of the probe–drogue aerial refueling system under aerodynamic disturbances, and proposes docking control method based on iterative learning control to compensate for the docking errors caused by aerodynamic disturbances. For receiver aircraft with different maneuverability, three control strategies are proposed to achieve a trade-off between safety and control precision. Furthermore, a practical method is proposed to predict the initial value of the learning controllers, which can significantly improve the iterative learning speed of the proposed methods. Finally, simulations demonstrate that the proposed control methods are simple and efficient for the docking control of autonomous probe–drogue aerial refueling. [ABSTRACT FROM AUTHOR]

This paper presents an additive-state-decomposition-based attitude tracking control method for a class of bank-to-turn aerial vehicles subject to unknown disturbances and nonlinear coupling. This method ‘additively’ decomposes the original tracking problem into two more tractable problems, namely a tracking problem for a deterministic nonlinear ‘primary’ system, and a disturbance rejection problem for a linear time-invariant ‘secondary’ system. Based on the decomposition, a backstepping controller is designed for the primary system to track the reference attitude signal, and a proportional-integral controller is applied to the secondary system to compensate for the disturbances. Finally, the two designed controllers are combined to achieve the original control objective. By using additive state decomposition, the proposed control method with two degrees of freedom can consider tracking task and disturbance rejection task respectively. Simulation results illustrate that the proposed controller can track the reference attitude signal and compensate for disturbances meanwhile. Additionally, the ASD-based controller outperforms the traditional backstepping controller in the presence of unknown disturbances and input delay, and the robustness of the full system can be improved by adjusting the controller parameters of the secondary system. [ABSTRACT FROM AUTHOR]

For multicopters, failures may abort missions, crash multicopters, and moreover, injure or even kill people. In order to guarantee flight safety, a system of prognostics and health management should be designed to prevent or mitigate unsafe consequences of multicopter failures, where health evaluation is an indispensable module. This paper proposes a health evaluation method of multicopters based on Stochastic Hybrid System (SHS). In the SHS model, different working conditions (health statuses) of multicopters are modeled as discrete states, and system behaviors of different working conditions are modeled as continuous dynamics under discrete states. Then, the health of multicopters is quantitatively measured by a definition of health degree, which is a probability measure describing an extent of system degradation from an expected normal condition. On this basis, the problem of multicopter's health evaluation is transformed to a hybrid state estimation problem. In this case, a modified interacting-multiple-model algorithm is proposed to estimate the real-time distribution of hybrid state, and evaluate multicopter's health. Finally, a case study of multicopter with sensor anomalies is presented to validate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Multicopters have been attracting increasing attention in recent years, while it is significant to consider the flight safety of multicopters in the presence of propulsor faults or failures. Therefore, this paper presents a methodology to analyze the controllable probability of a multicopter with arbitrary configurations based on controllability theory and an available control authority index. The methodology is then used to analyze the controllable probability of multicopters with different propulsor numbers and configurations to show its effectiveness. Based on the controllable probability results, an optimal configuration method is given. [ABSTRACT FROM AUTHOR]

Autopilot systems on unmanned aerial vehicles (UAVs) are safety-critical systems whose requirements on reliability and safety are ever-increasing. However, testing a complex autopilot control system is an expensive and time-consuming task, which requires massive outdoor flight tests during the whole development stage. This paper presents an indoor automatic test platform for autopilot systems aiming to significantly improve the development efficiency and safety level of UAVs. First, a unified modeling framework is proposed for different types of aerial vehicles to make it convenient to share common modeling experience and failure modes. Then, a real-time simulation platform is developed by using automatic code generation and FPGA-based hardware-in-the-loop simulation methods to ensure simulation credibility on software and hardware levels. Finally, an automatic test framework is proposed to traverse test cases during real-time flight simulation and assess the test results. In the verification part, the accuracy and credibility of the simulation platform are verified by comparing the obtained results with experimental results, and several successful applications on multicopters demonstrate the practicability of the proposed platform. [ABSTRACT FROM AUTHOR]

Aerial refueling is an important capability to increase the endurance and flight range of aircraft, but it often suffers from a low success rate. The altitude and speed of the tanker aircraft in the docking phase play a great role in the docking success rate. According to this, the optimal trim state, namely the optimal speed and altitude of the tanker aircraft, is investigated through the reachability analysis method in this paper. The optimal problem is transformed to find the trim state corresponding to the maximum volume of the reachable set. First, a relative motion model of the receiver aircraft with respect to the drogue is proposed. Then, based on reachability analysis, an optimization problem is formulated and a solution procedure is given in detail. In the simulation, the volumes of reachable sets are plotted with respect to the given discrete speeds and altitudes, based on which the optimal trim state of the docking phase is determined. Finally, the determined optimal trim state is verified by using numerous docking control simulations and the degree of controllability from another aspect. The effectiveness of the proposed method is demonstrated. [ABSTRACT FROM AUTHOR]

Continuously encircling and monitoring an individual static target is an important application scenario for a multi-UAV system. In this paper, to address the problem of multi-UAV encircling the target arbitrarily, evenly and densely in 3D space, a distributed vector field control method with an annular virtual tube is proposed. Some Lyapunov-like functions are designed elaborately, and a formal analysis based on the invariant set theorem is made to show that all UAVs can complete the encirclement task successfully. Simulations and experiments are carried out to show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]