Predictive fault-tolerant control of an all-thruster satellite in 6-DOF motion via neural network model updating

The problem of controlling an all-thruster spacecraft in the coupled translational-rotational motion in presence of actuators fault and/or failure is investigated in this paper. The nonlinear model predictive control approach is used because of its ability to predict the future behavior of the system. The fault/failure of the thrusters changes the mapping between the commanded forces to the thrusters and actual force/torque generated by the thruster system. Thus, the basic six degree-of-freedom kinetic equations are separated from this mapping and a set of neural networks are trained off-line to learn the kinetic equations. Then, two neural networks are attached to these trained networks in order to learn the thruster commands to force/torque mappings on-line. Different off-nominal conditions are modeled so that neural networks can detect any failure and fault, including scale factor and misalignment of thrusters. A simple model of the spacecraft relative motion is used in MPC to decrease the computational burden. However, a precise model by the means of orbit propagation including different types of perturbation is utilized to evaluate the usefulness of the proposed approach in actual conditions. The numerical simulation shows that this method can successfully control the all-thruster spacecraft with ON-OFF thrusters in different combinations of thruster fault and/or failure.     

热防护系统损伤容限分析

建立了含初始矩形损伤的热防护系统(Thermal protection system,TPS)气动热分析的CFD数值模型,分析结果表明损伤区域侧壁出现了很高的热流密度峰值,并且迎风面侧壁峰值高于背风面,而损伤区域底部热流密度却很低。利用分析获得的热流密度建立了含损伤和无损伤TPS的有限元传热分析模型。分析结果表明:损伤的存在导致防热瓦最高温度急剧上升,超过其材料能承受的极限温度(1 500℃),防热瓦首先失效,而损伤对机体最高温度影响较小。最后进行了TPS损伤容限分析,在防热瓦极限温度约束下,外部热流密度最大值从100kW/m2增加到140kW/m2,矩形损伤宽度最大容许值从22.7mm减小到12.6mm,而弧形损伤宽度最大容许值从34.6mm减小到25.1mm,即随着外部热流密度最大值增加,损伤宽度的最大容许值降低,并且相同外部热流密度水平下弧形损伤宽度的最大容许值大于矩形损伤。     

基于深度学习的空间站舱内服务机器人视觉跟踪

为提升舱内跟随服务机器人的任务辅助能力,解决机器人对航天员的视觉跟踪问题,提出了一种基于深度学习和概率模型的人体视觉跟踪算法。利用深度卷积神经网络实现了对穿着多样、姿态任意人体的稳定检测。结合人体检测结果,设计了运动预测概率模型,实现了对指定人员准确、连续的跟踪。算法对包含大多数航天员活动的多个数据集进行了验证。实验结果表明:提出的跟踪算法实现了对穿着多样、姿态任意人体的稳定跟踪,并有效避免了由于穿着相似、遮挡可能造成的误跟踪问题。该算法为空间站舱内跟随服务机器人对航天员的视觉跟踪提供了有效的解决方法。算法基于融合的RGB-D图像,工程上易于构建和实现,也可拓展到其他跟随服务机器人视觉跟踪任务中。     

软着陆验证试验中月面特性模拟方法

月面特性的模拟是月面软着陆验证试验的重要设计因素。文章结合探测器的设计状态和试验需求,论述了月面特性模拟的具体要求;基于月面地形统计分布规律,实现了月面原始形貌的模拟;通过高程剔除设计和模块化组合设计,实现了对多种典型月貌的快速模拟;最后通过月表反射特性的模拟,全面满足了试验要求,并取得了良好的试验效果。文中所述的模拟方法可为我国后续行星表面探测器及着陆技术的验证提供借鉴。     

A boundary vector cell model of place field repetition

Hippocampal place cells are thought to form the neural substrate of a global cognitive map. However, in multicompartment mazes, these cells exhibit locally repeating representations, undermining the global cognitive map view of place cells. This phenomenon appears to be related to the repetitive layout of these mazes, but still no hypothesis adequately explains it. Here, we use a boundary vector cell (BVC) model of place cell firing to model the activity of place cells in numerous multicompartment environments. The activity of modeled place cells bears a striking resemblance to experimental data, replicating virtually every major experimental result. Our results support the BVC model and indicate that locally repeating place cell firing could result purely from local geometry.     

直升机惯性传感器结构的模态优化

提出了一种基于迭代抽样和径向基插值的自适应代理模型方法。这种自适应方法以减少仿真计算数量和提高代理模型自适应能力为目的,使用多岛遗传算法选择新增样本点并使新增样本点位于设计空间的稀疏区域,使得所有的样本点均匀分布于设计空间。标准误差用来判断代理模型的精度大小以决定是否对代理模型进行更新。这种自适应代理模型结合多岛遗传算法对直升机的惯性传感器结构模态进行优化。用拉丁超立方抽样方法选择10个样本点构建初始的代理模型,自适应代理模型的计算结果表明2%的误差条件下需要额外增加7个样本点。优化结果表明不同的权重系数对最优模态特性的影响很大,惯性传感器结构的一至六阶模态值更加远离直升机的激励频率。     

Development and performance evaluation of tropospheric scintillation model on Ku-band satellite link over Akure,Nigeria

Existing amplitude scintillation prediction models often perform less satisfactorily when deployed outside the regions where they were formulated. This necessitates the need to evaluate the performance of scintillation models developed in one region using data data from other regions while documenting their relative errors. Due to its variation with elevation angle, frequency, other link parameters and meteorological factors, we employed three years (January 2016 to December 2018) of concurrently measured satellite radio beacons and tropospheric weather parameters to develop a location-based amplitude scintillation prediction model over the Earth-space path of Akure (7.17^oN, 5.18^oE), South-western Nigeria. The satellite beacon measurement used Tektronix Y400 NetTek Analyzer at 1 s integration time while meteorological parameters, namely; temperature, pressure and relative humidity were measured using Davis Vantage Vue weather station at 1 min integration time. Comparative study of the model’s performance with nine (9) existing scintillation prediction models indicates that the best and worst performing models, in terms of root mean square error (RMSE), are the Statistical Temperature and Refractivity (STN) and direct physical and statistical prediction (DPSP) models with values 11.48 and 51.03 respectively. Also, worst month analysis indicates that April, with respective enhancement and fade values of 0.88 and 0.90 dB for 0.01% exceedance, is the overall worst calendar month for amplitude scintillation.     

蜂窝状薄壁管拉伸时的内陷分析

蜂窝材料因具备广阔的结构设计空间,已广泛应用于航空航天等工业领域。探索蜂窝元胞的组织结构、组分性质与材料整体性能之间的关系有助于新型功能性材料的设计开发。本文从非平面Vertex模型的势能形式出发,结合蜂窝薄壁圆管拉伸时的轴对称特征,通过变分法得到了圆管拉伸时母线满足的控制方程,揭示了边界效应是蜂窝状薄壁圆管受拉时产生内陷的原因,并结合母线控制方程的若干特解,考察了非平面Vertex模型势能形式中包含的材料性质参数与圆管拉伸后内陷程度及范围的关系。研究还指出,蜂窝材料的材料性质包含在非平面Vertex模型的势能形式中,为蜂窝状材料整体性能的研究提供了一种新的思路。