Precise line-of-sight modelling for angles-only relative navigation

This work presents a precise analytical model to reconstruct the line-of-sight vector to a target satellite over time, as required by angles-only relative navigation systems for application to rendezvous missions. The model includes the effects of the geopotential, featuring: the analytical propagation in the mean relative orbital elements (up to second-order expansion), the analytical two-way osculating/mean orbital elements’ conversion (second-order in $J_2$ and up to a given degree and order of the geopotential), and a second-order mapping from the perturbed osculating elements’ set to the local orbital frame. Performances are assessed against the line-of-sight reconstructed out of the precise GPS-based positioning products of the PRISMA mission. The line-of-sight modelled over a far-range one day long scenario can be fitted against the true one presenting residuals of the order of ten arc-seconds, which is below the typical sensor noise at far-range.     

A data-driven approach to modeling high-density terminal areas: A scenario analysis of the new Beijing,China airspace

Airports are being developed and expanded rapidly in China to accommodate and pro-mote a growing aviation market. The future Beijing Daxing International Airport (DAX) will serve as the central airport of the JingJinJi megaregion, knitting the Beijing, Tianjin, and Hebei regions together. DAX will be a busy airport from its inception, relieving congestion and accommodating growth from Beijing Capital International Airport (PEK), currently the second busiest airport in the world in passengers moved. We aim to model terminal airspace designs and possible conflicts in the future Beijing Multi-Airport System (MAS). We investigate standard arrival procedures and mathematically model current and future arrival trajectories into PEK and DAX by collecting large quantities of publicly available track data from historical arrivals operating within the Beijing terminal airspace. We find that (1) trajectory models constructed from real data capture aberrations and deviations from standard arrival procedures, validating the need to incorporate data on histor-ical trajectories with standard procedures when evaluating the airspace and (2) given all existing constraints, DAX may be restricted to using north and east arrival flows, constraining the capacity required to handle the increases in air traffic demand to Beijing. The results indicate that the termi-nal airspace above Beijing, and the future JingJinJi region, requires careful consideration if the full capacity benefits of the two major airports are to be realized.     

Hypersonic reentry trajectory planning by using hybrid fractional-order particle swarm optimization and gravitational search algorithm

This paper proposes a novel hybrid algorithm called Fractional-order Particle Swarm optimization Gravitational Search Algorithm (FPSOGSA) and applies it to the trajectory planning of the hypersonic lifting reentry flight vehicles. The proposed method is used to calculate the control profiles to achieve the two objectives, namely a smoother trajectory and enforcement of the path constraints with terminal accuracy. The smoothness of the trajectory is achieved by scheduling the bank angle with the aid of a modified scheme known as a Quasi-Equilibrium Glide (QEG) scheme. The aerodynamic load factor and the dynamic pressure path constraints are enforced by further planning of the bank angle with the help of a constraint enforcement scheme. The maximum heating rate path constraint is enforced through the angle of attack parameterization. The Common Aero Vehicle (CAV) flight vehicle is used for the simulation purpose to test and compare the proposed method with that of the standard Particle Swarm Optimization (PSO) method and the standard Gravitational Search Algorithm (GSA). The simulation results confirm the efficiency of the proposed FPSOGSA method over the standard PSO and the GSA methods by showing its better convergence and computation efficiency.     

含滑行时间约束的真空段弹道设计研究

由于动力系统及测控资源的约束,工程中存在着末级两次点火但滑行时间受限的运载火箭真空段弹道设计问题。基于线性引力场的假设,引入含滑行时间约束的切换条件,从而将含固定滑行时长的弹道优化问题转换成对两点边值问题的迭代求解和对运动方程的积分,并通过多个算例仿真验证了该方法的正确性和有效性。同时,研究了迭代过程中滑行段不同弹道预报方法对弹道设计的影响,结果显示较高的预报精度可以获得更优的弹道设计结果。该方法提供了一种新的弹道设计思路,在总体方案论证或初步设计阶段可以替代传统设计方法,以有效提升弹道设计效率,优化火箭方案。     

叶片磨抛机器人力/位混合控制的设计与实现

为提高航空类发动机叶片的自动化磨抛精度,减小复杂曲面叶片加工轨迹控制误差,采用基于六维力传感器的机器人力/位混合控制策略,实现机器人磨抛轨迹的在线修正。搭建以Staubli机器人和ATI六维力传感器为核心部件的叶片磨抛验证平台,通过C++开发上位机,采集磨抛过程中六维力传感器信息并进行Kalman滤波。通过示教确定机器人运动轨迹,对机器人运动轨迹与力传感器信息进行采集分析,确定基于力/位混合控制可以实现机器人运动轨迹的在线修正,为复杂曲面的叶片磨抛轨迹控制提供一种解决方案。     

High-fidelity trajectory optimization for aeroassisted vehicles using variable order pseudospectral method

In this study, the problem of time-optimal reconnaissance trajectory design for the aeroassisted vehicle is considered. Different from most works reported previously, we explore the feasibility of applying a high-order aeroassisted vehicle dynamic model to plan the optimal flight trajectory such that the gap between the simulated model and the real system can be narrowed. A highly-constrained optimal control model containing six-degree-of-freedom vehicle dynamics is established. To solve the formulated high-order trajectory planning model, a pipelined optimization strategy is illustrated. This approach is based on the variable order Radau pseudospectral method, indicating that the mesh grid used for discretizing the continuous system experiences several adaption iterations. Utilization of such a strategy can potentially smooth the flight trajectory and improve the algorithm convergence ability. Numerical simulations are reported to demonstrate some key features of the optimized flight trajectory. A number of comparative studies are also provided to verify the effectiveness of the applied method as well as the high-order trajectory planning model.     

混合遗传算法在航天器最优交会中的应用

推导了航天器双冲量交会时的优化模型,以此为基础构造了最优交会的燃料-时间混合优化指标,并针对基本遗传算法局部搜索能力不强的问题,提出一种将最速下降法与遗传算法相结合的混合遗传算法,其中下降搜索的优化方向利用每一代中最劣个体所包含的优化信息获得。数值计算表明,该混合算法可加速算法的收敛,具有良好的优化性能和函数适应能力。最后,对共面圆轨道双冲量交会情况进行了仿真计算,仿真结果表明混合遗传算法的设计是成功的。     

基于CPSO的UAV编队集结路径规划

针对多无人机编队集结路径规划问题,提出了具有合作机制的分布式协同粒子群(CPSO)算法。为了满足无人机运动学约束,采用曲率连续的PH曲线作为备选路径。基于协同进化思想提出CPSO算法,为每架无人机规划出一条满足机间协同约束的最优安全可飞行路径。仿真结果表明,规划得到的多条路径能够满足无人机运动学约束、安全性及无人机之间的协同性要求;相比于协同进化遗传算法,CPSO算法搜索成功率更高,稳定性更好。     

基于混合粒子群算法的上升段交会弹道快速优化设计

基于梯度搜索的高效性和粒子群搜索的随机性,提出了一种混合粒子群算法,并应用该算法研究了运载火箭上升段交会弹道快速优化设计问题.以运载火箭与目标飞行器在交会时刻的距离最小为目标函数,设计了运载火箭飞行程序,建立了运载火箭上升段交会弹道优化模型,同时分别采用混合粒子群算法、遗传算法和粒子群算法进行求解.仿真结果表明:基于本文算法对运载火箭上升段交会弹道进行优化设计,平均交会位置误差为4.137m,较遗传算法减少了17.940m,平均优化耗时488.922s,较粒子群算法缩短了2342.125s.混合粒子群算法搜索速度较快,收敛精度较高,可用于运载火箭上升段交会弹道的快速优化设计.      

航天器交会远程快速自主制导方法

针对近地近圆轨道航天器交会任务,设计了基于经典轨道要素的远程快速自主制导算法.对于任意初始纬度幅角偏差的远程导引,通过建立纬度幅角偏差与半长轴偏差的关系,将远程导引段分为初始轨道飞行、调相轨道飞行和调整轨道飞行3个阶段.初始轨道飞行进行轨道共面修正和调相机动;在调相轨道飞行期间,进行自然调相以及调相轨道到调整轨道的机动;调整轨道飞行阶段进行追踪航天器的远地点高度和近地点高度的修正,以及再次共面修正.所有变轨机动都以制导脉冲的形式给出,并都在轨道特殊点执行.精确轨道仿真验证了远程快速自主接近制导算法的可行性.