基于虚拟目标的导弹越肩发射初制导轨迹优化

摘要： 对具有攻角约束的空空导弹越肩发射轨迹优化问题做出研究.针对空空导弹越肩发射初制导段拐弯问题,设计了基于虚拟目标的程序指令. 基于最优控制的思想,利用高斯伪谱法求解最优程序指令,并根据所得指令的特点提出了三段式指令计算方法.在此基础上,比较了不同空域、速度以及虚拟目标位置条件对程序指令的影响.同时基于预测控制的思想,对程序指令进行在线修正,提高了导引指令的鲁棒性.三通道仿真结果表明,指令可以使导弹快速转弯并在转弯完成时指向虚拟目标.     

无人飞行器在线航迹规划技术研究

在线航迹规划是针对不确定环境中的航迹规划问题,无人飞行器需要在参考飞行航线的约束下,根据局部地形、地貌、障碍、威胁等信息以及飞机本身机动能力的限制,实时地计算出飞行航迹,并跟随该航迹完成飞行任务。阐述了无人飞行器在线航迹规划的结构框架,分析了无人飞行器动力学约束及威胁场约束,并根据航迹几何建模方法及在线规划算法的国内外研究概况,着重探讨了在线规划算法如A＊算法、Dynapath算法及连续型粒子群优化算法。最后,阐述了无人飞行器在线航迹规划面临的关键问题及发展趋势。     

航空发动机叶片叶缘随形磨抛刀路规划

航空发动机叶片是整机核心零件,其制造量占到30%以上。叶片叶缘具有大弯扭复杂曲面、薄壁圆角半径微小渐变、精度要求苛刻等特征,末端工序磨抛的精度和品质直接决定整机的性能与寿命。人工仍然是叶片叶缘磨抛的主要手段,然而粉尘危害健康、经验依赖性强、零件一致性差等不足决定了自动化磨抛是必然趋势。叶片叶缘自动化磨抛多采用砂轮横磨或纵磨的刀路规划方式,存在刀路不连续且分行密集、力控制困难等不足,易造成叶缘局部过切,难以保证圆角轮廓创成。为此,建立了砂带包络叶缘的螺旋进给力控磨抛工艺,提出了面族与复杂曲面高阶切触的随形磨抛路径规划方法,实现了叶片叶缘的宽行高效磨抛。首先对叶缘区域进行横磨刀路规划,然后依照圆弧拟合曲线原理进行高阶切触式包络段再规划,最后进行横纵混合磨抛路径规划实现螺旋式连续进给。针对航空发动机叶片开展仿真和实验验证,结果表明所提出的方法相比于传统的横磨或纵磨方法,可将刀触点减少78.8%,轮廓精度由-0.06~+0.07 mm提高到-0.015~+0.05 mm,表面粗糙度由R_a>3.2 μm提高到0.175 μm,并且有效保证了叶缘轮廓形状,避免了过切现象。     

PDE solution to UAV/UGV trajectory planning problem by spatio-temporal estimation during wildfires

Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs) have been used in research and development community due to their strong potential in high-risk missions. One of the most important civilian implementations of UAV/UGV cooperative path planning is delivering medical or emergency supplies during disasters such as wildfires, the focus of this paper. However, wildfires themselves pose risk to the UAVs/UGVs and their paths should be planned to avert the risk as well as complete the mission. In this paper, wildfire growth is simulated using a coupled Partial Differential Equation (PDE) model, widely used in literature for modeling wildfires, in a grid environment with added process and measurement noise. Using principles of Proper Orthogonal Decomposition (POD), and with an appropriate choice of decomposition modes, a low-dimensional equivalent fire growth model is obtained for the deployment of the space–time Kalman Filtering (KF) paradigm for estimation of wildfires using simulated data. The KF paradigm is then used to estimate and predict the propagation of wildfire based on local data obtained from a camera mounted on the UAV. This information is then used to obtain a safe path for the UGV that needs to travel from an initial location to the final position while the UAV’s path is planned to gather information on wildfire. Path planning of both UAV and UGV is carried out using a PDE based method that allows incorporation of threats due to wildfire and other obstacles in the form of risk function. The results from numerical simulation are presented to validate the proposed estimation and path planning methods.     

基于改进多元优化算法的动态路径规划

为满足动态路径规划实时性强和动态跟踪精度高的需求,提出一种基于能够同时发现并追踪多条最优以及次优路径的改进多元优化算法(IMOA)的求解方法。首先,通过利用贝赛尔曲线描述路径的方法把动态路径规划问题转化为动态优化问题;然后,把相似性检测操作引入到多元优化算法(MOA)中,增加算法同时跟踪多个不同最优以及次优解的概率;最后,用IMOA对贝赛尔曲线的控制点进行寻优。实验结果表明:当最优路径由于环境变化而变为非优或者不可行时,利用IMOA对多个最优以及次优解动态跟踪的特点,能够快速调整寻优策略对其他次优路径进行寻优以期望再次找到最优路径;其综合离线性能较其他方法也有一定的提高。因此,IMOA满足动态路径规划的实际需求,适用于解决动态环境中的路径规划问题。     

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%.     

危险天气下基于多重Morphin算法的终端区三维实时改航方法

基于多重Morphin算法,建立了终端区 三维实时改航方法。该方法首先根据航空器当前飞行状态按不同的转弯角和爬升/下滑角生 成一组弧线,随后在每条弧线的末端按同样方式反复运行,形成若干条由弧线组成的路径, 最后对所有路径进行综合评估,找到当前时刻的改航路径。算例分析表明,该方法提供的改 航路径可以保证航空器运行的安全与高效,在危险天气出现时更加充分地利用终端区空域资 源,同时计算时间短、可行性高。     

飞船跳跃式再入第一次再入能量管理方法

针对探月飞船跳跃式再入第一次再入能量管理问题,设计了一种能量管理方法。首先,采用大倾侧角再入,快速进入能量管理阶段;然后,对能量耗散速度进行控制,并预估跃起点的能量以确定飞船的跃起时机;最后,在能量管理结束后按设计指令过渡到跃起点。为检验能量管理方法的有效性及鲁棒性,基于标准轨迹法设计制导律,并进行仿真分析。仿真结果表明,该能量管理方法能改善轨迹跟踪性能,提高再入制导方法的精度和鲁棒性,并避免飞船在一次再入和二次再入过程中出现较大过载的现象。