实际工程中混合模型的任务可靠性分配方法

随着可靠性工程在航空产业中的逐步开展,适合于实际工程中的可靠性分配方法变得日益重要,尤其对于实际工程中混合模型的任务可靠性指标分配来说,因其对应的可靠性模型一般为串、并联等混合的复杂模型,可靠性指标分配相当困难。本文将实际工程中常见的比例组合法和专家评分分配法有效地结合起来,为实际工程中混合模型的任务可靠性分配提供了一种简便易行的方法。     

一种改进的UAV三维航迹实时规划算法

航迹规划对于战场环境中无人机完成其作战任务具有非常重要的意义.针对真实战场环境中低空无人机的三维航迹实时规划问题,构建了一个更加真实的战场威胁精简模型;提出遗传个体的基因优劣对比度,改进一种共享小生境遗传算法中编码基因的遗传特性.经过改进,增大优化基因的遗传概率,实现提高小生境遗传算法的全局优化能力和收敛速度,增强航迹规划的实时性.对三维数字地形空间进行定长网格编码,将改进的小生境遗传算法应用于三维虚拟战场环境中的无人机航迹规划,实验验证了改进算法的有效性,并能满足在线航迹规划的实时性要求.     

多指标约束下考虑报废的可修复备件携行方案优化

针对任务期间普遍存在的故障件报废和备件多指标约束问题,提出了多层级装备的可用度近似评估方法及携行备件方案优化方法。首先通过忽略维修时间将考虑报废率的多层级可修件转化为单层级消耗件,进而利用伽马分布的可加性建立装备可用度评估模型。在此基础上以装备可用度、备件总质量为约束指标,以备件总体积最低为目标构建多约束备件优化模型。模型求解过程中引入拉格朗日因子,并采用边际算法对约束因子进行动态调整。算例中通过与仿真结果的对比、分析得出：当维修时间取值在部件等效平均寿命的一半以内时,提出的近似方法合理可行,平均误差小于5%。     

反导多传感器协同任务规划综述

针对反导作战多传感器协同任务规划的相关问题,结合反导作战的特点,探讨反导作战信息处理过程与多传感器协同任务规划的关系,并分析多传感器协同任务规划的内涵;在此基础上,梳理出多传感器协同任务规划涉及的关键技术,并综述多源信息综合处理、多传感器协同部署、协同跟踪、协同引导和协同识别等关键技术的研究现状;最后就多传感器协同任务规划的发展提出一些建议。     

非凸二次约束下航天器姿态机动路径迭代规划方法

针对复杂约束下航天器姿态机动路径规划问题,首先描述和分析了航天器姿态机动过程中面临的动力学和运动学约束、有界约束、姿态指向约束,把姿态指向约束利用非凸二次型进行表述;其次从能量最优角度出发,将该约束机动问题归纳为非凸二次约束二次规划问题;然后引入线性松弛技术,将该问题转化成双线性规划问题,求出其中一个变量的凸包络和凹包络,降低求解复杂度,从而求出原问题的一个线性松弛。同时为了提高求解精度,提出一种基于评价函数的迭代规划算法,利用线性松弛求出的解作为初值,通过评价函数进行迭代规划,最终求出原问题的最优解。仿真结果表明该方法不仅可以满足复杂的姿态约束,得到全局姿态优化路径,而且能够降低能量消耗。     

基于多智能体强化学习的空间机械臂轨迹规划

针对某型六自由度（DOF）空间漂浮机械臂对运动目标捕捉场景,开展了基于深度强化学习的在线轨迹规划方法研究。首先给出了机械臂DH （Denavit-Hartenberg）模型,考虑组合体力学耦合特性建立了多刚体运动学和动力学模型。然后提出了一种改进深度确定性策略梯度算法,以各关节为决策智能体建立了多智能体自学习系统。而后建立了"线下集中学习,线上分布执行"的空间机械臂对匀速直线运动目标捕捉训练系统,构建以目标相对距离和总操作时间为参数的奖励函数。最后通过数学仿真验证,实现了机械臂对各向匀速运动目标的快速捕捉,平均完成耗时5.4 s。与传统基于随机采样的规划算法对比,本文提出的自主决策运动规划方法求解速度和鲁棒性更优。     

Adaptive path planning for unmanned aerial vehicles based on bi-level programming and variable planning time interval

This paper presents an adaptive path planner for unmanned aerial vehicles (UAVs) to adapt a real-time path search procedure to variations and fluctuations of UAVs’ relevant performances, with respect to sensory capability, maneuverability, and flight velocity limit. On the basis of a novel adaptability-involved problem statement, bi-level programming (BLP) and variable planning step techniques are introduced to model the necessary path planning components and then an adaptive path planner is developed for the purpose of adaptation and optimization. Additionally, both probabilistic-risk-based obstacle avoidance and performance limits are described as path search constraints to guarantee path safety and navigability. A discrete-search-based path planning solution, embedded with four optimization strategies, is especially designed for the planner to efficiently generate optimal flight paths in complex operational spaces, within which different surface-to-air missiles (SAMs) are deployed. Simulation results in challenging and stochastic scenarios firstly demonstrate the effectiveness and efficiency of the proposed planner, and then verify its great adaptability and relative stability when planning optimal paths for a UAV with changing or fluctuating performances.     

技术成熟度评价方法及其在交会对接任务中的应用

介绍了技术成熟度等级和评价的概念,简述了技术成熟度评价在国外航天工程中的应用情况,提出了航天工程技术成熟度评价标准,包括开展技术成熟度评价的目的、技术成熟度的详细定义及其内涵,并以技术成熟度等级五级为例,给出了具有可操作性的评价细则以及实施要点,通过交会对接任务中运载火箭评价应用实例对技术成熟度评价的应用进行了说明。     

Preparation of the Biochip experiment on the EXPOSE-R2 mission outside the International Space Station

Biochips might be suited for planetary exploration. Indeed, they present great potential for the search for biomarkers – molecules that are the sign of past or present life in space – thanks to their size (miniaturized devices) and sensitivity. Their detection principle is based on the recognition of a target molecule by affinity receptors fixed on a solid surface. Consequently, one of the main concerns when developing such a system is the behavior of the biological receptors in a space environment. In this paper, we describe the preparation of an experiment planned to be part of the EXPOSE-R2 mission, which will be conducted on the EXPOSE-R facility, outside the International Space Station (ISS), in order to study the resistance of biochip models to space constraints (especially cosmic radiation and thermal cycling). This experiment overcomes the limits of ground tests which do not reproduce exactly the space parameters. Indeed, contrary to ground experiments where constraints are applied individually and in a limited time, the biochip models on the ISS will be exposed to cumulated constraints during several months. Finally, this ISS experiment is a necessary step towards planetary exploration as it will help assessing whether a biochip can be used for future exploration missions.     

基于混合整数线性规划的爬壁机器人路径规划

为研究City-Climber爬壁机器人在3D建筑物环境中的路径规划问题,基于混合整数线性规划(MILP,Mixed Integer Linear Programming),提出了一种适用于City-Climber的路径规划方法.为了用MILP方法解决避障问题,首先用限制机器人控制输入的方法对City-Climber的数学模型进行解耦和线性化,再介绍了用MILP方法对控制输入进行描述的数学表达式,并提出了适用于爬壁机器人的新型代价函数,最后以一个方形房间为运动环境,用AMPL和CPLEX优化软件,以及Matlab软件解算路径规划问题.仿真结果表明:MILP方法较好地解决了City-Climber在3D环境下的路径规划和避障问题.