Estimation of flexible space tether state based on end measurement by finite element Kalman filter state estimator

This paper proposes a novel finite element Kalman filter to estimate the unmeasurable state of space tether systems based on the measured state at its ends only. The finite element method calculates the unmeasurable internal state as the virtual measurement based on the dynamic model of the system by imposing the input of measured state at the boundary to the model using the Lagrange multiplier method in the spatial space. Combining the real and virtual measurement into a hybrid measurement model of the system, the full state is reconstructed and propagated in the temporal space by the extended Kalman filter. Two state-space system models, the dynamics-based and kinematics-based state models, in the Kalman filter are explored. The observability and stability of the newly proposed finite element Kalman filter are examined and proved. The advantages of the proposed state estimator are (i) the singularity in the virtual measurement of state caused by the number of internal state greater than the number of state measured at the boundary is eliminated in the statistic meaning by the Kalman filter, and (ii) the effects of noises of the observation data and the uncertainties of model discretization are considered and minimized. The correctness and effectiveness of the proposed state estimator is demonstrated by the numerical analysis of a space tether system orbiting around the Earth. The results show the proposed state estimator with only measured state at the ends of the tether successfully provides an accurate time history estimation of geometric configuration and motion of the entire tether. Moreover, the results also show the difference caused by the dynamics-based and kinematics-based system models in the state estimator is negligible. The kinematics-based system model should be used in the state estimator due to its significantly low computational load. Finally, the proposed method can be easily applied for the state estimation process for other space tethered spacecraft systems.     

Association of optical tracklets from a geosynchronous belt survey via the direct Bayesian admissible region approach

The direct Bayesian admissible region approach is an a priori state free measurement association and initial orbit determination technique for optical tracks. In this paper, we test a hybrid approach that appends a least squares estimator to the direct Bayesian method on measurements taken at the Zimmerwald Observatory of the Astronomical Institute at the University of Bern. Over half of the association pairs agreed with conventional geometric track correlation and least squares techniques. The remaining pairs cast light on the fundamental limits of conducting tracklet association based solely on dynamical and geometrical information.     

椭球状态定界的鲁棒算法

提出了一种计算鲁棒的线性离散时间系统的椭球状态定界算法.算法假设系统的过程和量测噪声以及初始状态由已知椭球来定界,然后利用椭球集合来描述系统真实状态的可行集.算法的时间更新和量测更新过程分别产生两个椭球的向量和与交.算法对椭球形状矩阵进行Cholesky分解,使得当存在舍入误差时椭球形状矩阵保持正定.为了不受病态矩阵求逆的影响,算法的量测更新过程采用了求次最小容积椭球的方法.采用在数字计算机上进行蒙特卡洛仿真来检验算法的性能.结果表明算法的精度与最优算法十分接近,并且具有很好的计算鲁棒性.算法同时具有易于在并行计算机上运行的优点.      

一种修正的马氏距离判别法

马氏距离判别法是一种基于马氏距离的多元统计分析方法,其引入了协方差矩阵的逆矩阵,以排除属性变量的量纲及变量之间的相关性对距离度量的干扰。然而,在属性变量存在严重的多重共线性时,样本协方差矩阵的奇异性会影响其逆矩阵估计的稳定性,从而降低马氏距离判别法的有效性。为此,提出了一种修正的马氏距离判别法,采用了一般交叉验证(GCV)方法,在属性变量间存在高度相关性的情况下,选择预测效果最好的变量维度,同时可以对协方差矩阵的逆矩阵进行稳定的估计。修正的马氏距离判别法可以得到可靠的协方差矩阵的估计,提高模型的判别准确率;也可以抵抗样本外的扰动,提高模型的泛化能力。仿真实验结果验证了在属性变量存在严重的多重共线性情形下,修正的马氏距离判别法的判别效果较经典的马氏距离判别法有明显的提升。      

Re-entry trajectory tracking of reusable launch vehicle using artificial delay based robust guidance law

A Reusable Launch Vehicle (RLV), during the re-entry phase of its flight, experiences uncertain environment and extreme turbulence. This calls for an effective control strategy to guide the vehicle efficiently on a trajectory that allows safer landing conditions while providing robustness against external disturbances and system uncertainties. In this regard, a Time-Delayed Control (TDC) strategy has been proposed to track the space vehicle on a predetermined trajectory in the presence of these uncertainties. In the proposed approach, the system vector and the uncertainties are lumped into a single function which is estimated using the input and output data from the previous instant. Theoretical analysis of the control strategy executed using Lyapunov’s method, proves Uniformly Ultimately Bounded (UUB) stability of the closed loop system. The efficacy of the proposed approach has been verified through simulation studies which affirm robust tracking of the optimal trajectory generated through Pseudo-Spectral method (PSM), in the presence of time-varying uncertainties.     

飞机总体协同优化中的一种混合混沌算法

针对协同优化应用中所碰到的计算困难,分析了现有改进方式。将系统级优化转化成无约束优化问题,选择智能优化算法是一种有效的解决方法,但应注意计算量的控制.将混沌优化和单纯形法相结合,构造出一种混合混沌算法.混沌能有效地跳出局部最优解而接近全局最优点,同时利用单纯形法在混沌优化解的邻域内局部寻优.用协同优化方法对某型干线客机进行总体方案设计;同时各学科级采用序列二次规划法,系统级采用混合算法寻优.计算结果表明此方法是有效的.      

基于神经网络的电液转台非线性积分滑模控制

针对高精度电液飞行仿真转台具有高度非线性、参数不确定和不确定非线性等特点,提出了一种基于RBF（Radial Basis Function）神经网络的非线性积分滑模鲁棒控制方法.采用自适应RBF神经网络对该系统存在的参数不确定性和不确定非线性进行补偿,从而降低滑模控制器对切换项的增益的需求,进而减小系统抖振幅值.积分滑模面的设计能消除外部干扰对系统带来的稳态误差.根据积分滑模变结构控制器的特点,将控制律分为等效控制律和到达控制律.等效控制律使系统运动于滑模面附近,到达控制律可使处于状态空间内任意初始位置的系统趋近于滑模面,并进一步通过Lyapunov方法证明了系统的渐近稳定性.实验结果表明,所提出的非线性控制器不仅能满足电液转台的高精度跟踪性能的要求,且对参数不确定性和不确定非线性具有一定的鲁棒性.     

Short-arc tracklet association for geostationary objects

Measurement association and initial orbit determination is a fundamental task when building up a database of space objects. This paper proposes an efficient and robust method to determine the orbit using the available information of two tracklets, i.e. their line-of-sights and their derivatives. The approach works with a boundary-value formulation to represent hypothesized orbital states and uses an optimization scheme to find the best fitting orbits. The method is assessed and compared to an initial-value formulation using a measurement set taken by the Zimmerwald Small Aperture Robotic Telescope of the Astronomical Institute at the University of Bern. False associations of closely spaced objects on similar orbits cannot be completely eliminated due to the short duration of the measurement arcs. However, the presented approach uses the available information optimally and the overall association performance and robustness is very promising. The boundary-value optimization takes only around 2% of computational time when compared to optimization approaches using an initial-value formulation. The full potential of the method in terms of run-time is additionally illustrated by comparing it to other published association methods.     

基于仅光学观测的短弧关联分析方法

初始轨道确定是空间目标编目的一个重要部分,尤其在光学仅角度观测下是极具挑战性的.光学观测在短弧的情况下很难进行有效的初轨确定,解决短弧问题的一个重要手段是将不同时刻获取到的短弧数据进行关联匹配,找到属于同一个目标的观测数据.以容许域的方法为基础,通过找到拟合多组观测数据的最优轨道的方式来确定角度预测值和角度测量真实值之...     

A multi-satellite co-tracking method for a single space target based on adaptive distributed spherical simplex information-weighted consensus filter

A multi-satellite co-tracking method for a single non-cooperative target is proposed to extend the arc of observation as well as to improve the accuracy of tracking. Firstly, the motion of the target is considered to be affected by J2 perturbation, and the model of multi-satellite co-tracking a single space target is designed with only measured angles. Then, a multi-satellite co-tracking method for a single space target based on an adaptive distributed spherical simplex information-weighted consensus filter (ADSSICF) is proposed. The spherical simplex is used to reduce the computational cost of the information filter, and to improve the efficiency of tracking. The angle-only measurement equation is linearized by the statistical linear regression method, and linearization errors are compensated for by updating measurement noise. By designing an adaptive consensus algorithm, only a small number of iterations are needed to achieve network consensus, to improve the convergence speed of the consensus algorithm, and prove the stability of ADSSICF. Finally, a simulation of four low-orbit satellites tracking a single space target is established. The focus of this paper is on the real-time performance and tracking accuracy of the multi-satellite co-tracking a single space target with angle-only based on ADSSICF. The performance of ADSSICF is verified from three indicators: the consensus and convergence of algorithm, the accuracy of state estimation.     

基于最小轨道交叉距离的小行星顺访探测目标预筛选方法

小行星探测有助于研究太阳系演化等重要科学问题,在深空探测任务转移途中实施小行星顺访探测可增加科学研究回报。直接通过轨道递推筛选小行星探测目标计算量大、效率低,针对该问题提出了基于最小轨道交叉距离的目标预筛选方法。在推导出适用于计算双曲线轨道的最小轨道交叉距离公式后,将此理论应用到小行星顺访探测目标筛选中。首先基于探测器与小行星轨道的形状、空间位置计算二者轨道在空间中的几何最近距离,预筛选出可能满足接近距离标准的小行星目标;然后基于轨道递推模型,筛选出真实最近距离小于可接近标准的目标小行星。仿真结果显示,基于最小轨道交叉距离的预筛选方法可有效减少计算量,降低计算时间,提高小行星顺访目标筛选的效率。      

基于灵敏度分析的结构-声学鲁棒优化设计

针对工程中普遍存在的结构-声场耦合系统,充分考虑系统本身及外载荷的不确定性,提出了求解系统响应范围的区间有限元分析方法及鲁棒优化设计模型.从耦合系统的平衡方程出发,利用中心差分方法得到了系统响应的灵敏度计算公式.引入区间变量来表征信息不足的不确定参数,借助一阶泰勒展式,可以快速估算系统响应的区间上下界.在结构鲁棒优化设计过程中,通过引入灵敏度指标,将原不确定单目标优化问题转化为确定的多目标优化问题.为保证结构性能更加稳定,利用区间可能度刻画约束条件的鲁棒性.数值算例通过某弹舱模型弹性板厚度的优化设计,验证了所建立的鲁棒优化模型及算法的有效性.      

Uncertainties in estimates of the risks of late effects from space radiation.

Methods used to project risks in low-Earth orbit are of questionable merit for exploration missions because of the limited radiobiology data and knowledge of galactic cosmic ray (GCR) heavy ions, which causes estimates of the risk of late effects to be highly uncertain. Risk projections involve a product of many biological and physical factors, each of which has a differential range of uncertainty due to lack of data and knowledge. Using the linear-additivity model for radiation risks, we use Monte-Carlo sampling from subjective uncertainty distributions in each factor to obtain an estimate of the overall uncertainty in risk projections. The resulting methodology is applied to several human space exploration mission scenarios including a deep space outpost and Mars missions of duration of 360, 660, and 1000 days. The major results are the quantification of the uncertainties in current risk estimates, the identification of factors that dominate risk projection uncertainties, and the development of a method to quantify candidate approaches to reduce uncertainties or mitigate risks. The large uncertainties in GCR risk projections lead to probability distributions of risk that mask any potential risk reduction using the "optimization" of shielding materials or configurations. In contrast, the design of shielding optimization approaches for solar particle events and trapped protons can be made at this time and promising technologies can be shown to have merit using our approach. The methods used also make it possible to express risk management objectives in terms of quantitative metrics, e.g., the number of days in space without exceeding a given risk level within well-defined confidence limits.     

基于小波神经网络的多传感器自适应融合算法

针对多传感器融合系统的非线性和不确定性,将小波分析与神经网络相结合,提出一种基于小波神经网络的多传感器自适应融合算法.融合系统包括扩展卡尔曼滤波器、小波神经网络、融合知识库以及航迹融合算法.该算法以分布式融合结构为基础,利用环境信息理论和测量方差归一化方法构建小波神经网络,并且通过数值样本训练小波神经网络,使其在融合过程中实时估计各传感器的信任度,再由融合知识库根据各传感器信任度来选择适合的航迹融合算法,最终得到全局状态估计.实验结果表明,提出的融合算法可以根据环境变化在线自适应融合来自多传感器的测量值,对不确定信息具有很好的融合能力.      

复合材料点阵夹芯梁振动特性区间分析与优化

考虑到复合材料的分散性,研究了复合材料点阵夹芯梁的自由振动特性.将不确定参数用区间向量进行定量化,提出高精度的含不确定参数复合材料点阵夹芯梁固有频率的配点型区间分析方法,该方法无需不确定参数的概率信息,只需明确不确定参数所在范围界限,进而实现复合材料点阵夹芯梁结构的不确定优化.该方法为解决非线性现象突出的新型复合材料设计等复杂问题提供了一个可行途径.与概率方法相比,区间分析方法的结果表明该方法是可行的.与确定性优化方法相比,区间优化方法在复合材料结构优化领域能够充分考虑结构潜在不确定性带来的不利影响,工程指导意义更为明显.     

基于滚动时域优化的旋转弹解耦控制器设计

旋转弹在飞行过程中会受到外界干扰和不确定性的影响,并且存在气动交联、惯性交联和控制交联,为了实现稳定飞行,有必要进行解耦控制器设计。提出了一种基于滚动时域优化（RHO）的解耦控制方法。将旋转弹和舵机系统的动力学模型用状态空间形式描述,基于旋转弹、指令滤波器、积分跟踪误差的状态方程得到一个增广状态方程。采用基于指令滤波器的滚动时域优化方法进行控制量解算,根据系统输出与指令信号之间的差值实时调节控制器增益,实现旋转弹解耦控制。从加速度控制仿真结果可以看出,所设计的控制系统基本不受转速、建模误差和外界干扰的影响,具有较高的鲁棒性。      

基于马氏距离的半监督鉴别分析及人脸识别

针对人脸识别应用中人脸样本的类别信息不足以及人脸样本特征间存在相关性的问题,提出了一种基于马氏距离的半监督鉴别分析.该方法在图嵌入框架下利用马氏距离对数据集中带有类别信息的样本进行边界Fisher分析,不仅保持了类内的紧致性和类间的分离性,而且抽取出有利于分类的鉴别特征,同时将不带类别信息的样本用于描述数据集的几何结构,保留了样本间的局部邻域信息.与传统的特征抽取方法相比,该方法有较好的识别性能,在ORL,YALE及AR人脸数据库上的实验验证了该方法的有效性.      

四旋翼无人机执行器可重构性量化评价方法研究

随着对系统安全性和可靠性要求的不断提高,故障系统的自主恢复能力即系统的可重构性受到高度关注,然而现有对于控制系统可重构性量化评价的方法主要针对线性系统,因此以具有强耦合、欠驱动、强非线性的四旋翼无人机（quadrotor UAV）为被控对象,提出了一种基于双滑模面鲁棒观测器与马氏距离结合的非线性系统可重构性量化评价方法。首先,在四旋翼无人机非线性模型的基础上,设计了具有对扰动和故障均不敏感的双滑模面鲁棒观测器,用于实现对系统状态的准确估计;其次,在执行器饱和及系统状态误差指标双约束条件下,采用基于马氏距离的相似度法,对非线性系统可重构性进行量化评价;最后,通过四旋翼无人机仿真实验验证了所提方法的有效性。结果表明,所提方法能够真实反映不同故障程度下系统的可重构性量化水平,为非线性故障系统控制策略调整补偿提供了重要依据。      

基于地磁坐标和Kriging技术的高纬地区f0F2重构方法

为能够在高纬区域获取高精度电离层参数特性结果,提出了基于地磁坐标的高纬度区域电离层F₂层临界频率（f₀F₂）的重构方法.该方法确定了基于地磁坐标的变异函数,通过求解改进Kriging方程得出估计值.方法的确定取决于对2种坐标系、2类电离层距离计算方法以及尺度因子的选取.通过对俄罗斯6个垂直探测站在太阳活动高年（2013年）和低年（2017年）的f₀F₂历史观测数据使用月中值进行交叉验证,证明了引入地磁坐标和利用球面距离计算方法对高纬度地区进行重构能够达到最优效果.相比现有方法,其整体标准误差和绝对误差均有所降低.上述研究证实了该方法的有效性,对电子信息系统的可用频率预测以及通信效能保障具有重要意义.