飞翼无人机进舰下滑纵向固有模态特性研究

针对舰载飞翼布局无人机与常规布局飞行器不同的气动外形,建立无人机飞行状态下附近流场的网格模型,并计算了该型无人机的气动参数。基于插值函数计算得出该型无人机的升力系数、阻力系数和俯仰力矩系数对于迎角变化的曲线。建立纵向小扰动方程进行仿真计算,求解出该型无人机在进舰下滑状态时的固有模态特性。计算结果表明,该模型在配平条件下可用于舰载飞翼布局无人机的着舰气动适配性研究。     

伴飞诱饵支援条件下无人飞行器协同作战效能研究

针对复杂的威胁环境，介绍了伴飞诱饵在体系作战条件下的应用情况；基于排队论的突防概率模型，研究了伴飞诱饵支援条件下，无人飞行器的协同突防概率和效费比：提出了作战体系作战时效性的概念；建立了火力对抗条件下无人飞行器打击防空导弹防御体系的Lanchester方程，利用所建模型分析了伴飞诱饵对作战时效性的贡献。研究表明，排队论和Lanchester方程用于伴飞诱饵条件下的无人飞行器协同作战效能研究是有效的。     

Aircraft robust multidisciplinary design optimization methodology based on fuzzy preference function

This paper presents a Fuzzy Preference Function-based Robust Multidisciplinary Design Optimization (FPF-RMDO) methodology. This method is an effective approach to multidisciplinary systems, which can be used to designer experiences during the design optimization process by fuzzy preference functions. In this study, two optimizations are done for Predator MQ-1 Unmanned Aerial Vehicle (UAV): (A) deterministic optimization and (B) robust optimization. In both problems, minimization of takeoff weight and drag is considered as objective functions, which have been optimized using Non-dominated Sorting Genetic Algorithm (NSGA). In the robust design optimization, cruise altitude and velocity are considered as uncertainties that are modeled by the Monte Carlo Simulation (MCS) method. Aerodynamics, stability and control, mass properties, performance, and center of gravity are used for multidisciplinary analysis. Robust design optimization results show 46% and 42% robustness improvement for takeoff weight and cruise drag relative to optimal design respectively.     

舰载无人机横侧向着舰控制律设计

舰载无人机横侧向控制一直是着舰控制律设计的难点。为了解决着舰横侧向控制的难题,针对舰载无人机的非线性模型采用了反演控制器设计方法,为解决传统反演的计算膨胀问题,引入了指令滤波方法,同时只设计了一个Lyapunov函数证明了稳定性;由于舰载机动力学模型不能精确获得,采用了自适应方法对其进行估计。设计的横侧向着舰控制器,能较好地解决横侧向控制器设计过程中的耦合问题,并且和传统PID进行了仿真对比,证明了所设计的控制律满足了对参考信号跟踪的性能要求。     

浅论无人机机载卫通天线尺寸与数字信号传输带宽关系

卫星通信是无人机中继通信的重要手段。本文对无人机卫星通信链路中飞机总体设计关注的机载卫通天线尺寸选择问题进行了较详细的计算、探讨。     

NOx emissions of turbofan powered unmanned aerial vehicle for complete flight cycle

Unmanned Aerial Vehicles (UAVs) have been getting more and more popular in both civil and military arena. Similar to manned aircraft, their propulsion systems or engines emit harmful gases such as nitrogen oxides. Since UAVs have different mission profiles and operational parameters than manned aircraft, it is worthy to investigate their NO_x emissions. Therefore, in this study, NO_x emissions of a turbofan powered UAV for complete flight cycle was calculated and optimized within a range of altitude and speed parameters. NO_x emissions were calculated based on ICAO ground test data and corrected to any speed and altitude during flight legs using both Boeing Fuel Flow Method 2 and DLR Fuel Flow Method. Total NO_x emissions were calculated for complete flight cycles for different altitude and speed parameters. Numerical results were presented graphically and additionally optimization studies were conducted. Optimization studies include determination and comparison of speed and altitude for minimum NO_x emissions by the two fuel flow methods and maximum loiter time achievable by UAV.     

Robustness evaluation method for unmanned aerial vehicle swarms based on complex network theory

Unmanned Aerial Vehicle (UAV) swarms have been foreseen to play an important role in military applications in the future, wherein they will be frequently subjected to different disturbances and destructions such as attacks and equipment faults. Therefore, a sophisticated robustness evaluation mechanism is of considerable importance for the reliable functioning of the UAV swarms. However, their complex characteristics and irregular dynamic evolution make them extremely challenging and uncertain to evaluate the robustness of such a system. In this paper, a complex network theory-based robustness evaluation method for a UAV swarming system is proposed. This method takes into account the dynamic evolution of UAV swarms, including dynamic reconfiguration and information correlation. The paper analyzes and models the aforementioned dynamic evolution and establishes a comprehensive robustness metric and two evaluation strategies. The robustness evaluation method and algorithms considering dynamic reconfiguration and information correlation are developed. Finally, the validity of the proposed method is verified by conducting a case study analysis. The results can further provide some guidance and reference for the robust design, mission planning and decision-making of UAV swarms.     

多旋翼无人机在某测控设备标校工作中的应用

为了提高综合测控设备标校效率，简化标校流程，克服传统标校的各项缺点，进行了多旋翼无人机在某综合测控设备标校工作中的应用研究。分析了某综合测控设备相位标校工作的现状，对引入多旋翼无人机进行相位标校工作进行了需求分析，建立了无人机相位标校的数学模型。在选定无人机型号、设计实现小型化信标机、飞行电池与信标机固定支架等工作的基础上，实现了无人机在某综合测控设备相位标校工作上的应用。经过实际标校工作检验，多旋翼无人机不但能应用于某综合测控设备相位标校工作中，而且同时能够检验综合测控设备的动态跟踪性能，在同类型设备中具有一定的推广应用价值。     

无人机系统基地级维修模式研究

分析了国内军用无人机系统发展现状，根据新时期无人机系统维修保障的需求，提供了二级维修体制中基地级维修保障模式和方法。对完善无人机系统维修保障模式进行了初步设计。     

基于军网的无人机远程维修保障及模拟训练专家系统研究

为解决无人机维修保障力量薄弱的问题，本文提出了一种基于军网技术的远程维修保障和模拟训练智能专家系统。首先对专家系统的结构模型和功能模型进行了设计，其次阐述了用户管理模块、远程故障诊断模块、可视化模块、数据库维护模块、模拟训练模块等5个专家系统的主要功能模块的实现方法，最后介绍了专家系统的安全防护措施。分析表明，该专家系统可以提高无人机维修保障效率，提升维修保障人员故障诊断能力。