交会对接任务碰撞规避策略制定研究简

针对交会对接任务目标飞行器与追踪器轨道运行特性,综合考虑规避策略计算方法与工程实际相结合的问题,提出高度规避、时间规避以及与正常轨控相结合的碰撞规避策略计算方法等三种空间目标碰撞规避策略计算方法.高度规避计算方法采用了Lambert飞行原理,用简化二体开普勒模型取代高精度轨道预报方法,迭代求解规避机动速度增量,实现了通过约束过交点与目标径向距离差得到速度增量的最优解;时间规避计算方法通过轨道周期与速度增量的关系,实现了通过约束过交点与目标的时间差得到速度增量的最优解;与正常轨控相结合的碰撞规避策略计算方法,在正常控制考虑冗余控制量的基础上,对控制策略的控制开始时间或沿迹方向的速度增量进行较小的修正,使两者通过碰撞点的时刻或径向距离错开,达到碰撞规避的目的,该方法不仅可以节省燃料、而且对任务的影响较小.通过对三种空间目标碰撞规避策略计算方法仿真分析结果表明,完全适用于交会对接任务,可为我国载人航天任务飞行安全提供技术保障.     

基于SOC的ACAS无线电高度信号激励测试的设计

本文介绍了一种以SOC为核心芯片用于机载防撞系统(ACAS)中符合ARINC552A标准无线电高度信号激励测试的软硬件设计方法.采用C8051F020型SOC芯片及OPA552等芯片搭建仿真电路,利用PDIUSBD12接口芯片建立与工控机的通讯,依据ARINC552A标准,用C51编写仿真控制程序,将仿真的ACAS无线...     

基于势函数法的航天器自主姿态机动控制

主要研究存在禁止姿态的航天器自主姿态机动控制问题.首先,给出航天器的动力学和运动学模型,利用四元数描述航天器与机动姿态和禁止姿态的姿态偏差,用相应的欧拉转角描述不同姿态间的距离.为利用势函数完成禁止姿态回避,结合航天器的运动情况设计排斥势函数(RPF)存在条件后,根据禁止姿态最小允许夹角构造一种新的排斥势函数.接着,利...     

基于避障伪距离的自由漂浮空间机器人规划跟踪一体化控制

针对自由漂浮空间机器人(Free Floating Space Robot,FFSR)的避障规划与控制问题,提出一种FFSR的避障规划-跟踪一体化控制方法。首先,基于障碍物伪距离技术,采用FFSR逆几何模型求解期望末端位姿下的连杆伪距离估计值,进而通过求解非线性优化问题,获得FFSR避障期望轨迹。其次,将全局轨迹规划与局部在线避障相结合,辅以离散状态黎卡提方程（DSDRE）控制方法实现FFSR的避障规划-跟踪一体化控制。最后,采用6R空间机器人模型验证了所提方法的有效性。仿真结果表明,该方法能够实现FFSR的避障控制,有效克服了传统FFSR控制中末端轨迹规划与控制相分离的问题,提高了FFSR的环境适应性。     

基于蚂蚁算法的星上ATM交换结构

对于卫星ATM交换系统，星上ATM交换结构的设计是一个非常重要的部分。由于卫星通信具有带宽有限、时延受限、信道误码率高等特点，因而设计星上交换结构时必须尽可能降低交换时延，减少内部阻塞。为此，提出一种基于蚂蚁算法的星上ATM交换结构，并对此方案进行了分析和仿真。结果表明，该结构由于采用了蚂蚁算法和阻塞规避方案，有效改善了信元时延和信元丢失率等性能。     

基于DDPG-PID的机器人动态目标跟踪与避障控制研究

针对机器人在动态复杂环境下的操作问题,研究机械臂跟踪运动目标及避障的运动控制方法。采用传统PID控制方法与DDPG强化学习算法相结合的方式,利用PID控制使得机械臂的工作平面快速接近目标物并与之重合,再使用DDPG算法让机械臂在平面内自主学习追踪目标物投影同时避开障碍物投影,最终在三维空间中实现跟踪与避障。该方法将机械臂作为一个智能体,智能体通过感知目标物和障碍物的距离偏差来自主学习避障跟踪策略。将本方法用于多自由度机械臂路径规划与避障任务中,对比单纯使用DDPG算法将机械臂作为智能体在空间中进行决策控制,仿真结果显示本文所提出的方法收敛效果和控制性能更好,机械臂能在训练后实现目标物的稳定跟踪和障碍物的躲避。     

A strategic flight conflict avoidance approach based on a memetic algorithm

Conflict avoidance （CA） plays a crucial role in guaranteeing the airspace safety. The cur- rent approaches, mostly focusing on a short-term situation which eliminates conflicts via local adjust- ment, cannot provide a global solution. Recently, long-term conflict avoidance approaches, which are proposed to provide solutions via strategically planning traffic flow from a global view, have attracted more attentions. With consideration of the situation in China, there are thousands of flights per day and the air route network is large and complex, which makes the long-term problem to be a large-scale combinatorial optimization problem with complex constraints. To minimize the risk of premature convergence being faced by current approaches and obtain higher quality solutions, in this work, we present an effective strategic framework based on a memetic algorithm （MA）, which can markedly improve search capability via a combination of population-based global search and local improve- ments made by individuals. In addition, a specially designed local search operator and an adaptive local search frequency strategy are proposed to improve the solution quality. Furthermore, a fast genetic algorithm （GA） is presented as the global optimization method. Empirical studies using real traffic data of the Chinese air route network and daily flight plans show that our approach outper- formed the existing approaches including the GA .based approach and the cooperative coevolution based approach as well as some well-known memetic algorithm based approaches.     

基于比例导引角度线性化的无人机避障研究

基于无人机与障碍物之间的几何关系,在极坐标系下建立了无人机与障碍物之间的运动学方程,通过引入基于角度线性化的比例导引律,使无人机能够顺利避开障碍物。引入的基于角度线性化的比例导引律是关于无人机相对速度航向角与避障点视线角的函数,由比例函数及偏差函数组成。为解决初始时刻相对速度航向角不满足引入导引律的问题,在调节函数中加入了指数项。通过稳定性证明,得到了满足要求的导引律参数取值范围。最后对设计的避障算法进行了仿真,仿真结果验证了算法的有效性。     

A multi-aircraft conflict detection and resolution method for 4-dimensional trajectory-based operation

Conflict Detection and Resolution(CDR) is the key to ensure aviation safety based on Trajectory Prediction(TP). Uncertainties that affect aircraft motions cause difficulty in an accurate prediction of the trajectory, especially in the context of four-dimensional(4D) Trajectory-Based Operation(4DTBO), which brings the uncertainty of pilot intent. This study draws on the idea of time geography, and turns the research focus of CDR from TP to an analysis of the aircraft reachable space constrained by 4D waypoint constraints. The concepts of space–time reachability of aircraft and space–time potential conflict space are proposed. A novel pre-CDR scheme for multiple aircraft is established. A key advantage of the scheme is that the uncertainty of pilot intent is accounted for via a Space-Time Prism(STP) for aircraft. Conflict detection is performed by verifying whether the STPs of aircraft intersect or not, and conflict resolution is performed by planning a conflict-free space–time trajectory avoiding intersection. Numerical examples are presented to validate the efficiency of the proposed scheme.     

Neural adaptive control for a ground experiment of the space proximity operation in a six-degree-of-freedom micro-gravity simulation system

In this study, a neural adaptive controller is developed for a ground experiment with a spacecraft proximity operation. As the water resistance in the experiment is highly nonlinear and can significantly affect the fidelity of the ground experiment, the water resistance must be estimated accurately and compensated using an active force online. For this problem, a novel control algorithm combined with Chebyshev Neural Networks (CNN) and an Active Disturbance Rejection Control (ADRC) is proposed. Specifically, the CNN algorithm is used to estimate the water resistance. The advantage of the CNN estimation is that the coefficients of the approximation can be adaptively changed to minimize the estimation error. Combined with the ADRC algorithm, the total disturbance is compensated in the experiment to improve the fidelity. The dynamic model of the spacecraft proximity maneuver in the experiment is established. The ground experiment of the proximity maneuver that considers an obstacle is provided to verify the efficiency of the proposed controller. The results demonstrate that the proposed method outperforms the pure ADRC method and can achieve close-to-real-time performance for the spacecraft proximity maneuver.