超临界翼型低雷诺数流动分析及优化设计

以高空长航时无人机(UAV)翼型研究为背景,对超临界RAE2822翼型在高空高亚声速下的低雷诺数气动特性进行了数值模拟及优化设计研究。采用求解雷诺平均N-S方程的有限体积法,对典型低雷诺数下RAE2822翼型绕流进行数值模拟,验证了SST k-ω湍流模型的可靠性和准确性;基于不同高度不同雷诺数下RAE2822翼型的计算气动力对比分析,研究了高度增大所带来的低雷诺数效应;通过对低雷诺数下超临界翼型表面流场结构及流动机理的详细分析,提出了一种弱化激波的翼型设计思想,并通过优化算例验证了该思想的可行性。     

高性能飞机发展对控制理论的挑战

根据笔者30余年来飞行试验研究的实践,从实际飞行的角度简要综述了影响飞行安全的大迎角过失速机动、超低空重载空投、飞行器突发故障和无人机控制方法研究。描述了操纵稳定性飞行试验获取飞机模型的手段和通常飞行控制器设计对模型的近似,给出了8个飞行鲁棒控制的研究问题;对超低空重载空投控制方法进行了描述,并给出了飞行器出现故障时突变模型和容错控制方法;同时,描述了测量对飞行控制特别是对保障无人机飞行安全的重要性,指出了飞行控制方法研究存在的部分问题,并建议有关高校研究单位从稳定性很好的四旋翼转向固定翼或单旋翼战术无人机等高层次研究。     

基于信息一致性的无人机紧密编队集结控制

提出了基于信息一致性的分段式无人机紧密编队集结控制策略,将集结过程分为3步:参考集结点选取和目标集结点分配、形成松散编队以及形成紧密编队。首先,以线切入预定航线的方式计算参考集结点,按照松散编队队形展开生成目标集结点,并利用基于三维距离空间的优化选择算法,将目标集结点快速、准确地分配给每架无人机。然后,使用速度一致性实现向目标集结点定点集结和向松散编队伴航集结,通过非精确的航迹控制快速形成松散编队,提高编队集结的效率。接下来,启动速度、姿态一致性来实现编队最终的精确航迹控制,并逐步压缩编队队形进入紧密编队,避免发生碰撞,完成从松散编队到紧密编队的平稳过渡,同时准确地跟踪预定航线。使用协同修正方法抑制了测量误差、协同误差和通信延迟,提高了紧密编队的稳定性和控制精度。最后,基于MATLAB平台环境对所提三维集结控制策略进行了仿真,验证了其合理性与有效性。     

UAV navigation in high dynamic environments: A deep reinforcement learning approach

Unmanned Aerial Vehicle (UAV) navigation is aimed at guiding a UAV to the desired destinations along a collision-free and efficient path without human interventions, and it plays a crucial role in autonomous missions in harsh environments. The recently emerging Deep Reinforcement Learning (DRL) methods have shown promise for addressing the UAV navigation problem, but most of these methods cannot converge due to the massive amounts of interactive data when a UAV is navigating in high dynamic environments, where there are numerous obstacles moving fast. In this work, we propose an improved DRL-based method to tackle these fundamental limitations. To be specific, we develop a distributed DRL framework to decompose the UAV navigation task into two simpler sub-tasks, each of which is solved through the designed Long Short-Term Memory (LSTM) based DRL network by using only part of the interactive data. Furthermore, a clipped DRL loss function is proposed to closely stack the two sub-solutions into one integral for the UAV navigation problem. Extensive simulation results are provided to corroborate the superiority of the proposed method in terms of the convergence and effectiveness compared with those of the state-of-the-art DRL methods.     

Effects of pressure oscillation on aerodynamic characteristics in an aero-engine combustor

The effects of pressure oscillation on aerodynamic characteristics in an aero-engine combustor are investigated. A combustor test rig is designed to simulate the pressure drop characteristics of a practical annular combustor. The pressure drop characteristics are firstly measured under atmosphere condition with non-reacting flow (or cold flow), and the air mass flow proportion of each component (dome/liner) are obtained; these properties are base lines for comparison with combustion state. The combustion tests are then carried out under conditions of inlet temperature 340–450 K, fuel air ratio 0.010–0.028. The stability map and the oscillation frequencies are obtained in the tests, the results show that pressure oscillation amplitude increases with the increase of fuel air ratio. Phase trajectory reconstruction is applied to classify the pressure oscillation motion; there are three motions captured in the tests including: “disk”, “ring” and “cluster”. The pressure drops across the dome under strong pressure oscillation are distinctly divergent from the cold flow, and the changes of pressure drops are mainly affected by pressure oscillation amplitude, but is less influenced by pressure oscillation motion nor oscillation frequencies. Based on the mass flow conservation, the reduction of effective flow area of combustor under strong pressure oscillation is demonstrated. Liner wall temperatures are analyzed through Multiple Linear Regression (MLR) method to estimate the reduction of the air mass flow proportion of the liner cooling under strong pressure oscillation. Finally, the air mass flow proportions of each component under strong pressure oscillation are estimated, the results show that the pressure oscillation motion also has influence on air mass flow proportion.     

An intelligent target detection method of UAV swarms based on improved KM algorithm

Complete and efficient detection of unknown targets is the most popular application of UAV swarms. Under most situations, targets have directional characteristics so that they can only be successfully detected within specific angles. In such cases, how to coordinate UAVs and allocate optimal paths for them to efficiently detect all the targets is the primary issue to be solved. In this paper, an intelligent target detection method is proposed for UAV swarms to achieve real-time detection requirements. First, a target-feature-information-based disintegration method is built up to divide the search space into a set of cubes. Theoretically, when the cubes are traversed, all the targets can be detected. Then, a Kuhn-Munkres (KM)-algorithm-based path planning method is proposed for UAVs to traverse the cubes. Finally, to further improve search efficiency, a 3D real-time probability map is established over the search space which estimates the possibility of detecting new targets at each point. This map is adopted to modify the weights in KM algorithm, thereby optimizing the UAVs’ paths during the search process. Simulation results show that with the proposed method, all targets, with detection angle limitations, can be found by UAVs. Moreover, by implementing the 3D probability map, the search efficiency is improved by 23.4%–78.1%.     

Aerodynamic performance of owl-like airfoil undergoing bio-inspired flapping kinematics

Natural flyers have extraordinary flight skills and their prominent aerodynamic performance has attracted a lot of attention. However, the aerodynamic mechanism of birds' flapping wing kinematics still lacks in-depth understanding. In this paper, the aerodynamic performance of owl-like airfoil undergoing bio-inspired flapping kinematics extracted from a free-flying owl wing has been numerically investigated. The overset mesh technique is used to deal with the large range movements of flapping airfoils. The bio-inspired kinematics consist of plunging and pitching movement. A pure sinusoidal motion and a defined motion composed of plunging of sinusoidal motion and pitching of the bio-inspired kinematics are selected for comparison. The other two NACA airfoils are also selected to figure out the advantages of the owl-like airfoil. It is found that the cambered owl-like airfoil can enhance lift during the downstroke. The bio-inspired kinematics have an obvious advantage in lift generation with a presence of higher peak lift and positive lift over a wider proportion of the flapping cycle. Meanwhile, the bio-inspired motion is more economical for a lower power consumption compared with the sinusoidal motion. The sinusoidal flapping motion is better for thrust generation for a higher peak thrust value in both upstroke and downstroke, while the bio-inspired kinematics mainly generate thrust during the downstroke but produce more drag during the upstroke. The defined motion has similar lift performance with the bio-inspired kinematics, while it consumes more energy and generates less thrust. The unsteady flow field around airfoils is also analyzed to explain the corresponding phenomenon. The research in this paper is helpful to understand the flight mechanism of birds and to design a micro air vehicle with higher performance.     

基于双ARM的无人直升机飞控导航系统设计

将两片基于ARM(Advanced RISC Machine)内核的微控制器应用于某型共轴式无人直升机飞控导航系统的CPU(Central Processing Unit)模块,连同电源及舵机信号处理模块、信号处理及接口模块形成一个高度集成的嵌入式飞控导航计算机,提供的8路异步串行通讯接口、8路数字信号口,与组合导航设备、信号调理设备、收发电台和姿态稳定系统与舵机等外围设备连接构成一套完整的无人直升机数字式飞控导航系统,另配置了16 MB FLASH(Flash Eeprom)用于任务与飞行状态数据记录,并基于ADS(ARM Developer Suite)集成开发环境编制了系统的飞控与自主导航软件.经地面检测与调试,该系统运行情况良好.     

盘旋跟踪地面目标小型无人机控制系统设计

针对一种大展弦比、V形尾翼常规布局小型无人机盘旋跟踪地面目标飞行的飞行控制策略进行了研究.采用了一种单轴光电探测系统修正视场纵向误差,无人机航向控制修正视场横向误差的控制方法.设计了一种自适应PID(Proportion Integration Differention)控制器,并通过对无人机六自由度非线性运动模型的建模分析,进行了控制律的仿真验证,并将算法融合在盘旋跟踪飞行实验中.仿真及实际飞行实验结果表明:该控制系统在突风等大扰动的影响下获得了良好的动态性能指标,并有效地抑制了飞机姿态通道对视轴通道的耦合影响,满足了飞行任务的需求.     

超小型直升机动力学模型的建模、辨识与验证

为实现超小型直升机的自动控制飞行,需建立较为精确的动力学模型.考虑机体、主旋翼/稳定杆和尾桨间的耦合对飞行动态特性的影响,建立了AF25B型超小型直升机的连续线性时不变系统模型.设计并配置了机载设备,完成在遥控飞行状态下的飞行数据采集与存储.通过时域系统辨识方法,辨识了直升机在悬停状态下的模型参数,并对辨识结果进行验证和分析,表明所建模型能充分反映该型直升机悬停状态下的动态特性.