Experimental study on transfer functions of an active rotor under different flight conditions

Vibrations impose negative impacts on the effectiveness and public acceptance of helicopters. Active rotors with trailing-edge flaps have been proved to be an effective way to actively eliminate helicopter vibrations. For the existing control algorithm based on offline system identification, the transfer functions of an active rotor under different flight conditions are pre-requisites to implement closed-loop vibration control. In this study, a three-bladed active rotor with improved trailing-edge flaps is designed, and wind-tunnel tests are conducted to identify the transfer functions of this active rotor using frequency sweep and phase sweep methods. The experimental results demonstrate that these transfer functions are insensitive to the variation of flight speeds: the amplitude of the transfer function varies slightly, while the phase delay almost remains unchanged. In addition, this finding is validated through closed-loop vibration control tests with the active rotor. The transfer function obtained from the hover test results is also applicable to closed-loop vibration control tests under the forward flight conditions. This will dramatically simplify the implementation and operation of an active rotor.     

Energy-efficient data collection for UAV-assisted IoT: Joint trajectory and resource optimization

Internet of Things (IoT) can be conveniently deployed while empowering various applications, where the IoT nodes can form clusters to finish certain missions collectively. As energy-efficient operations are critical to prolong the lifetime of the energy-constrained IoT devices, the Unmanned Aerial Vehicle (UAV) can be dispatched to geographically approach the IoT clusters towards energy-efficient IoT transmissions. This paper intends to maximize the system energy efficiency by considering both the IoT transmission energy and UAV propulsion energy, where the UAV trajectory and IoT communication resources are jointly optimized. By applying large-system analysis and Dinkelbach method, the original fractional optimization is approximated and reformulated in the form of subtraction, and further a block coordinate descent framework is employed to update the UAV trajectory and IoT communication resources iteratively. Extensive simulation results are provided to corroborate the effectiveness of the proposed method.     

Contributions to data transmission at critical moments on unmanned aerial vehicles

As for unmanned aircraft, the knowledge of the aircraft performance is directly related with the navigation, guidance, and control system programming. Therefore, the measured data in each phase of the flight must be sufficiently precise to obtain a good characterization of aircraft. This article proposes new methods of sending information to ground, which make it possible to know the aircraft behavior accurately, and for this purpose, four contributions have been made for ALO (Avión Ligero de Observación, Spanish acronym for Light Observation Aircraft). Currently, the characterization is based on data obtained at ten samples per second, insufficient to acquire detailed knowledge of what happened during the whole flight of an aircraft. As a result of these contributions, many more samples per second of accelerations and angular velocities are obtained at the most critical moments of the flight, such as takeoff or landing. Among the improvements included are data compression techniques, providing references to locate the measured data in time and identifying labels of each parameter.     

Distortion minimization for multimedia transmission in NOMA HAP-UAV integrated aerial access networks

Aerial access networks have been envisioned as a promising 6G solution to enhance the ground communication systems in both coverage and capacity. To better utilize the spectrum and fully explore different channel characteristics, this paper constructs an integrated network comprising the High Altitude Platform (HAP) and Unmanned Air Vehicles (UAVs) with the Non-Orthogonal Multiple Access (NOMA) technology. In order to improve the transmission quality of images and videos, a power management scheme is proposed to minimize the distortion of the transmissions from the HAP and UAVs to the terminals. The power control is formulated as a non-convex problem constrained by the maximal transmit power and the minimal terminal rate requirements. The variable substitution and the first-order Tailor’s expansion is used to transform it into a sequence of convex problems, which are subsequently solved through the gradient projection method. Simulation demonstrates the signal distortion and error rate improvement achieved by the proposed algorithm.     

基于SiP的低成本微小型GNC系统技术

随着微机电系统(MEMS)技术及微惯性器件的发展,大量小型化、低成本、高性能的导航、制导与控制(GNC)产品正越来越多地应用于小型无人飞行器、地面无人系统以及精确制导弹药等领域.针对各类应用需求,基于MEMS惯性测量单元(IMU)、GNSS接收模块、全捷联红外/可见光/激光多模智能导引头、信息处理器(DSP)与数据链通信模块,采用SiP技术研制出GNC芯片.基于GNC芯片构建一体化微小型GNC系统,突破了基于SiP一体化微小型GNC系统集成、全捷联红外/可见光/激光多模智能感知、嵌入式深组合导航、全捷联多模智能导引头/导航/制导与控制一体化设计等关键技术,并对其性能进行了评估.微小型GNC系统技术为低成本小型无人系统和精确制导弹药的发展夯实技术基础.     

非死锁合同网协议驱动的多机分布式时序任务分配

针对多无人机协同任务分配的时序约束问题，提出了基于非死锁合同网协议(DF CNP)的分布式时序任务分配方法，从理论上避免任务死锁，提升分配结果最优性。定义了局部信息条件下时序任务死锁判据，通过检测时序任务图环路状态与顶点可达性，判定分配方案的全局死锁状态，保证分配结果的可行性。定制了最近邻-深度优先混合搜索算法，在合同网排序过程中优先选择最近邻任务，并结合死锁判据递归回溯，在分布式架构下并行生成满足死锁约束的任务排序方案，提升分配结果的最优性。仿真对比结果表明：相比于非死锁遗传算法(TB GA)，DF CNP在求解效率方面具有显著优势；与耦合约束一致性束算法(CBBA TCC)相比，DF CNP结果最优性明显提升。     

一种超视距组网无人机载通信系统设计

针对超视距集群作业需求，提出将Ka频段高通量卫星技术与TD-LTE协议区域组网技术相结合，构建一种“1+N”架构的无人机载测控通信系统。通过方案介绍，阐述了卫星、组网、载荷等模块的设计思路、方案选型及实物设计结果，明确核心单元特点。详细论述了异构网络通信、平滑低延时传输、信源加密等关键技术，并完成链路余量计算、带宽时延测试及飞行试验。试验结果表明：系统任意终端间双向通信稳定可靠，方案设计合理可行。相比于卫星、组网单模通信方式，系统在长航距集群测控、任务协同、临场机动及应用资费等方面具有明显优势，为后续构建空天一体化多平台支撑通信系统，提供工程实践参考。