Deployment dynamics for flexible deployable primary mirror of space telescope with paraboloidal and laminated structure by using absolute node coordinate method

A nonlinear dynamic modeling method for primary mirror of Flower-like Deployable Space Telescope (F-DST) undergoing large deployment motion is proposed in this paper. To ensure pointing accuracy and attitude stability of the paraboloidal primary mirror, the mirror is discretized into equal thickness shell elements by considering shell curvature. And the material nonlinear constitutive relation of flexible mirror is acquired using Absolute Nodal Coordinate Formulation (ANCF). Furthermore, the primary mirror of F-DST can be regarded as a clustered multi-body system, and its dynamic equations of elastic deformation and deployment motion are established by virtual work principle. Finally, the deployment motion of primary mirror by different driving conditions are simulated, the results show that the vibrations of mirrors that driven by elastic hinge device are more than that driven by servo motor. In addition, single sub-mirror deployment process will perturb the pointing accuracy of primary mirror, and the multiple sub-mirrors simultaneously deploying will seriously affect all the sub-mirrors surface accuracy because of the coupling effect. Thus, there are theoretical value and practical significance for the controlling surface accuracy and attitude accuracy of space telescope.     

空间绳系机器人捕获目标后的面内自适应回收方法

在空间绳系机器人(TSR)捕获目标星后,操作机构与目标星形成质量、惯量和系绳连接点位置等参数未知的组合体,且系绳长度、偏角与组合体姿态严重耦合,控制输入严格受限,回收控制十分困难。针对其回收难题,综合考虑系绳长度、系绳偏角与组合体姿态,利用拉格朗日法建立了轨道面内的动力学模型,并基于动态逆理论设计了一种自适应抗饱和回收控制方法。首先,在对组合体质量、惯量与系绳连接点进行在线估计的基础上,设计一种自适应动态逆回收控制器;然后,设计辅助变量对控制输入进行补偿,解决控制输入受限问题;最后进行仿真验证。仿真结果表明,在线估计器能够快速有效地估计组合体动力学参数,回收控制系统能够利用受限的控制输入克服抓捕时刻的系绳偏角和组合体姿态扰动,并沿设计的回收轨迹实现稳定有效回收。     

A Carrier Synchronization Algorithm for Autonomous Radio Receiver in Deep Space

The carrier synchronization algorithm of the autonomous radio for deep space is studied. When the signal modulation is unknown, this paper improves the existing universal carrier synchronization loop for multiple modulations, expands the frequency tracking range of the loop, proposes a Tong detection-based M-ary Phase Shift Keying (M-PSK) signal locking detection algorithm to rapidly and effectively determine whether the current phase discrimination mode matches the modulation mode, so as to independently choose whether to switch the phase discrimination mode. Through theoretical analysis and comparison, it is described that the total detection probability of the algorithm proposed in this paper is significantly higher than the probability of single lock detection. Simulation results show that the algorithm has high detection probability and low computational complexity at a low signal to noise ratio.      

非合作目标交会的双层MPC全局轨迹规划控制

针对空间非合作目标近距离视线交会中的全局最优鲁棒轨迹规划与控制问题,提出了基于高斯伪谱方法（GPM）和线性时变模型预测控制（LTVMPC）的双层模型预测控制（MPC）算法。在轨迹规划方面,以视线坐标系下的相对轨道动力学为模型、能量最少和控制精度最优为性能指标构建最优控制问题,利用GPM精度高、收敛速度快的特点将最优控制问题转化为易于求解的全局非线性规划问题,在MPC框架下求解得到全局最优的标称轨迹,克服了传统的MPC不适用于全局大范围非线性规划的缺点;在轨迹跟踪控制方面,考虑预测时域内状态转移矩阵的时变特性,设计了LTVMPC算法对标称轨迹进行追踪,避免了存在不确定性时轨迹的重规划,从而降低在线计算量,保证算法在线自主实施,并且采用滚动优化的策略使算法对不确定性具有鲁棒性。由于规划层和控制层考虑的约束相同,因此规划的轨迹是可控、可达的。数字仿真表明,在燃料消耗和交会时间等方面,提出的方法均显著优于传统的MPC方法,相较于传统的MPC方法,新算法的交会时间减少50%左右,燃料消耗降低30%以上。     

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.     

火星进入段探测器自校准状态估计

由于大气密度、气动参数、突风和沙尘暴等因素的影响,火星探测器在进入段高速飞行的动力学模型中往往带来未知输入,这些未知输入使传统的滤波方法出现较大的偏差。研究采用一种新的自校准扩展Kalman滤波方法,对火星进入段的探测器进行状态估计,可以成功地消除这些未知输入带来的影响。数值仿真结果表明,该方法能有效提高导航精度。     

多普勒跟踪测量用于时空引力检验的尝试:(Ⅰ)理论建模

作为多普勒跟踪测量用于时空引力检验的尝试,在多普勒建模过程中加入了对于局部洛仑兹不变性(LLI)以及局部位置不变性(LPI)的检验参数。LLI/LPI是包括广义相对论在内的任何度规引力理论的基石。通过迭代求解多普勒建模过程中所需的光行时解,证明了只有在单程以及三程多普勒测量中可以检验LLI和LPI。鉴于该种测量手段无需额外载荷以及我国测控精度,可以尝试通过单/三程多普勒测量来检验LLI和LPI的科学目标。     

嫦娥三号月面巡视器机械臂就位探测规划

提出了一种基于SA *算法的嫦娥三号月面巡视器机械臂就位探测规划方法。建立了机械臂的正逆运动学模型,满足机械臂与环境不存在干涉的约束条件,并通过碰撞检测避免机械臂与环境和巡视器本体发生干涉;利用SA *算法在机械臂的工作空间进行搜索,在机械臂位形切换次数最少的优化条件下,实现了月面巡视器机械臂就位探测规划;通过月面巡视器在轨任务执行数据验证了基于SA *算法的月面巡视器机械臂就位探测任务的可行性。     

压缩氮气驱动的高速气炮实验技术

文章介绍压缩氮气驱动的二级气炮、三级气炮的研制背景、设计技术和发射性能特点,分析活塞质量、弹丸质量、驱动气压和泵管初充气压等发射参数对发射弹速和发射效果的影响,分析了制约提高弹速上限的主要因素,还介绍利用上述二级气炮和三级气炮开展的若干实验研究情况,评估压缩氮气驱动多级气炮的开发应用前景。     

一种空间极低温吸附制冷机的设计与实现

针对极低温吸附制冷技术的热沉制冷系统,系统分析了极低温吸附制冷的特性,研究了热沉温度对极低温吸附制冷性能的影响,研制了一台极低温吸附制冷机样机,工质气体为氦4,在1.5W@4.2K G-M制冷机基础上实现了50μW@0.8K的制冷性能,验证了基于机械制冷系统的更高热沉温度技术的可行性,这一成果为深空探测和载人空间站相关研究提供了技术支撑。