Automated design architectures for co-orbiting spacecraft swarms for planetary moon mapping

This work describes the design and optimization of spacecraft swarm missions to meet spatial and temporal visual mapping requirements of missions to planetary moons, using resonant co-orbits. The algorithms described here are a part of Integrated Design Engineering and Automation of Swarms (IDEAS), a spacecraft swarm mission design software that automates the design trajectories, swarm, and spacecraft behaviors in the mission. In the current work, we focus on the swarm design and optimization features of IDEAS, while showing the interaction between the different design modules. In the design segment, we consider the coverage requirements of two general planetary moon mapping missions: global surface mapping and region of interest observation. The configuration of the swarm co-orbits for the two missions is described, where the participating spacecraft have resonant encounters with the moon on their orbital apoapsis. We relate the swarm design to trajectory design through the orbit insertion maneuver performed on the interplanetary trajectory using aero-braking. We then present algorithms to model visual coverage, and collision avoidance in the swarm. To demonstrate the interaction between different design modules, we relate the trajectory and swarm to spacecraft design through fuel mass, and mission cost estimations using preliminary models. In the optimization segment, we formulate the trajectory and swarm design optimizations for the two missions as Mixed Integer Nonlinear Programming (MINLP) problems. In the current work, we use Genetic Algorithm as the primary optimization solver. However, we also use the Particle Swarm Optimizer to compare the optimizer performance. Finally, the algorithms described here are demonstrated through numerical case studies, where the two visual mapping missions are designed to explore the Martian moon Deimos.     

非结构混合网格自适应并行技术

计算流体力学（CFD）模拟实际工程问题所采用的网格规模可达千万量级，并行技术是减少计算时间的有效方法。耦合流场信息的网格自适应技术能有效动态优化计算网格，被NASA视为一项亟待发展的CFD关键技术。混合网格自适应系统包含网格分布优化、表面网格投影和空间网格匹配等关键技术。针对以上3项关键技术分别建立了高效的并行算法。首先，提出了"先唯一后同一"的两步法策略实现了网格单元分布优化过程的并行相容性；其次，基于局部曲面拟合思想，实现了曲面重构和新增物理网格点投影的完全并行；再次，提出了空间网格匹配技术的半并行算法，快速解决了网格单元交错问题。为了提高后续流场计算的并行效率，发展了基于并行重分区-网格数据迁移方法的动态负载平衡技术，并采用圆柱激波流场自适应模拟对动态负载平衡技术进行初步验证。最后，采用三角翼自适应加密测试了自适应系统的并行效率。结果表明，建立的混合网格自适应系统并行效率较高，且相比流场求解耗费总时间的比例低于1%。     

GPS广域增强系统电离层延迟网格修正算法的研究

建立了一种广域增强系统地面监测网对电离层延迟的观测数据生成网格修正值算法,并在天津,长春,西安三地通过用双频接收机同时采集的电离层延迟实测数据,对广域增强系统的电离层网格修正法的修正精度进行验证,并与一般用户目前采用的Ｋｌｏｂｕｃｈａｒ模型修正法进行了比较,结果表明,电离层延迟网格修正法的修正精度普遍大于８０％,优于Ｋｌｏｂｕｃｈａｒ模型修正法,是一种精度较高的电离层实时修正法。     

求解线性矛盾方程组的递推Householder变换法

 求解线性矛盾方程组是工程实践中经常遇到的问题。目前主要采用法方程组解法和基于各种正交变换的三角化解法。由于法方程组系数矩阵的病态条件数是原矛盾方程组系数矩阵病态条件数的平方,所以计算精度较差,有时甚至得到完全错误的结果。因此一些计算精度要求高的问题和高阶方程组的求解,多采用三角化法。但是,三角化法只能进行一次性处理,尚未出现随数据更新的实时递推算法。许多需要在线处理和数据存储最大的问题,只好采用一般递推最小二乘法。     

一种高精度角速率圆锥补偿算法

以角速率信号作为算法输入时,采用以往常用的圆锥补偿算法,算法误差明显增大.鉴于光纤陀螺角速率信号可以直接获取,提出了一种以角速率信号作为圆锥补偿算法输入的新补偿算法.在姿态更新周期内,以光纤陀螺角速率信号作为输入,求得陀螺角速率输出的表达式,结合旋转矢量微分方程,推导出新圆锥补偿算法表达式,然后以算法漂移误差最小对新算法进行优化.采用规则进动、典型的圆锥运动以及有噪声干扰的圆锥运动作为测试输入,通过与传统算法的对比,新算法计算量低、计算简单方便,算法精度高.新算法的提出为高动态环境下光纤陀螺捷联系统的姿态误差补偿提供了一个新的思路.     

一种求非线性规划全局最小解的算法

在评述了近２０年来发展的全局最优化方法之后，提出了一种求解全局最优化问题的算法，即从一个求得的局部最小解点出发，去解一个最大化问题，这个最大化问题是构造一个辅助函数去寻求一个更好的局部最优解，这样就产生一个局部最小解序列，得后得到全局最小解，另外还有了全局收敛性定理，也给出了数值例子。     

State of art on energy management strategy for hybrid-powered unmanned aerial vehicle

New energy sources such as solar energy and hydrogen energy have been applied to the Unmanned Aerial Vehicle(UAV), which could be formed as the hybrid power sources due to the requirement of miniaturization, lightweight, and environmental protection issue for UAV. Hybrid electrical propulsion technology has been used in UAV and it further enforces this trend for the evolution to the Hybrid-Powered System(HPS). In order to realize long endurance flight mission and improve the energy efficiency of UAV, many researching works are focused on the Energy Management Strategy(EMS) of the HPS with digital simulation, ground demonstration platforms and a few flight tests for the UAV in recent years. energy management strategy, in which off-line or on-line control algorithms acted as the core part, could optimize dynamic electrical power distribution further and directly affect the efficiency and fuel economy of hybrid-powered system onboard.In order to give the guideline for this emerging technology for UAV, this paper presents a review of the topic highlighting energy optimal management strategies of UAV. The characteristics of typical new energy sources applied in UAV are summarized firstly, and then the classification and analysis of the architecture for hybrid power systems in UAV are presented. In the context of new energy sources and configuration of energy system, a comprehensive comparison and analysis for the state of art of EMS are presented, and the various levels of complexity and accuracy of EMS are considered in terms of real time, computational burden and optimization performance based on the optimal control and operational modes of UAV. Finally, the tendency and challenges of energy management strategy applied to the UAV have been forecasted.     

基于平衡核函数聚类的飞行航迹数据分析方法

目前,使用数据挖掘的方法对目标的飞行航迹进行分析来确定航迹类别具有许多应用价值。飞行航迹数据具有维数高、交连多、可分类性能差等特点,要做到尽可能精确的聚类和分类十分困难。文章立足提高飞行航迹数据聚类分析的准确性,在航迹特征数据的预处理阶段,提出了一种平衡核函数的K-均值聚类方法,可以解决高维特征数据带来的奇异性,还能提高交叠样本的聚类性能;设计了一种模糊支持向量机的算法框架实现航迹的分类。通过实际飞行航迹数据集测试了设计框架下航迹聚类和分类识别的有效性,在实际工程上具有广泛的应用前景。     

非确定结构系统区间分析的直接优化法

工程中的非确定性问题可以用区间分析、随机理论或模糊集理论进行求解。本文采用区间分析法来处理结构静力分析和设计中的不确定性问题。将结构系统中的不确定性参数用区间数来表示,用有限元法建立系统的控制方程。该控制方程是线性区间方程组。本文讨论了一些求解区间线性方程组的方法并提出了一种直接优化法。将方程组中的所有区间数都作为设计变量,区间量的变化区间作为相应的设计变量的边界约束,运用约束优化法求出方程组解的各元素的最大值和最小值。文中给出了两个算例,列出了本文算法与其他算法的结果比较