采用PQLF的不确定模糊系统最优保性能控制

对一类模有界的参数不确定T-S模糊系统的保性能控制问题进行了分析研究。一个二次指标函数表征了闭环系统的性能。采用分段二次Lyapunov函数(Piecewise quadratic Lyapunov function,PQLF)方法,在使闭环系统渐近稳定的前提下以线性矩阵不等式(Linear matrix inequality,LMI)的形式给出了一种鲁棒最优保性能控制律。同时提出了一种新型分段并行补偿(Parallel distributed compensation,PDC)控制策略。该PDC控制器同样反映了模糊系统前提变量的规则结构信息。数值仿真显示,采用该设计方法所得到的闭环保性能值优于传统二次Lyapunov函数(Common quadratic Lyapunov function,CQLF)方法下的闭环保性能值,且系统动态性能良好,鲁棒性强。     

POD降阶算法中对基模态表达的改进

由一系列已知的相近流场解重新组合成一组正交分解(POD)的基模态。利用这些模态的线性组合构造绕一任意翼型的流场,使计算的未知量数目仅为所取相近解流场个数,而传统方法的未知量数目为网格单元数的4倍,因此极大地减少了未知量的数目,将其用于翼型优化,计算量会显著减少。给定的一系列相近流场解,是通过计算快照得到的,这些快照是形成正交模态的根本,直接影响近似计算的准确程度。本文提出了一种新的扰动方法,即通过扰动翼型的关键控制点反求翼型函数得到快照。通过几个已知的翼型解对子空间的投影比较可以看出,该方法的空间表达能力优于常用的加局部凸起的H icks-H enne函数的方法,而且近似计算的准确程度也更好。最后,探讨了正交分解的必要性,阐明利用POD降阶模型方法计算流场可以迅速收敛的内在原因。     

流量预测下智能寻优门限值的AOS帧生成算法

针对AOS空间通信系统的自适应帧生成算法帧生成时间门限值需要人工设置问题,提出一种流量预测下智能寻优门限值的AOS帧生成算法.该算法使用小波神经网络对ON/OFF模型产生的自相似流量进行预测,根据预测流量计算复用效率和平均包时延,使用人工鱼群算法对建立的综合评价函数进行智能寻优,从而得到帧生成算法的最佳门限值.该算法可...     

航天器零推进剂姿态机动启发式规划方法

针对零推进剂姿态机动约束耦合,导致规划效率低的问题,提出一种基于约束评价启发式的差分进化算法。基于零推进剂姿态机动约束分析,在规划空间中建立约束评价函数,对航天器约束和控制力矩陀螺约束进行解耦分类处理。设计基于约束评价函数的启发式策略,用于改进差分进化算法的种群变异,主动控制规划进程,引导零推进剂姿态机动规划序列满足多种约束,得到安全的姿态机动路径和控制力矩陀螺框架角路径。最后,数值仿真结果验证了该方法能够实现航天器零推进剂姿态机动规划。     

解析壁面函数的可压缩效应修正研究

基于适用于不可压缩流动的解析壁面函数,针对可压缩湍流边界层特征,考虑壁面网格内对流项变化和能量方程中黏性耗散项的影响,提出一种适用于可压缩流动的解析壁面函数。基于二维超声速和高超声速激波湍流边界层干扰流动,完成了粗网格高雷诺数k-ε模型加标准壁面函数、原始解析壁面函数、可压缩修正解析壁面函数和密网格低雷诺数Lauder-Sharma k-ε模型的对比计算。结果表明:四种湍流效应模拟策略都可以准确预测壁面压力和摩擦系数,而本文发展的考虑对流项分布和黏性耗散项影响的解析壁面函数不仅消除了原始解析壁面函数的非物理振荡,而且大幅提升了壁面函数壁面热流的预测精度,与密网格解最大差异不超过40%,预测结果接近于密网格低雷诺数模型结果,而标准壁面函数和原始解析壁面函数预测的壁面热流符号相反,且数值最大差异达500%。对于Ma5斜激波边界层干扰算例,本文构造的壁面函数计算时间仅为低雷诺数模型的5%左右,相较于其它壁面模型,计算时间仅增加了1%。     

A variational Bayesian-based robust adaptive filtering for precise point positioning using undifferenced and uncombined observations

In the application of precise point positioning (PPP), especially in the dynamic mode, the classical Kalman filter (KF) usually produces a large number of estimation errors or diverges when there are gross errors in the observation data or unexpected turbulences occur in target motion state or both of them. For such problem, a variational Bayesian (VB)-based robust adaptive Kalman filtering (VB-RAKF) is proposed in this paper. This filter introduces a classification robust equivalent weight function to resist observation gross error and the inverse Wishart prior to model inaccurate process noise covariance matrix (PNCM). To improve the instantaneous accuracy of state estimation, the VB approach is used to obtain better estimations of inaccurate PNCM. Several sets of observation data collected by IGS reference stations and vehicles are employed to check the robustness and positioning accuracy of the VB-RAKF model. The results show that the VB-RAKF algorithm is more robust than the KF, and can effectively resist the gross error in observation data and control state disturbance. In the IGS reference station tests, when compared to the KF, the static positioning accuracies of the VB-RAKF in the north, east and up directions are improved by 13%, 8% and 22%, respectively, and the simulated dynamic positioning accuracies of the VB-RAKF in the north, east and up directions are improved by 19%, 9% and 21%, respectively. The in-vehicle dynamic test verifies that the VB-RAKF outperforms the KF, and shows that the VB-RAKF has better performance than the KF when dealing with observation data which has obvious gross errors, and similar performance as the KF when gross errors are small.     

Reliability estimation of rotary lip seal in aircraft utility system based on time-varying dependence degradation model and its experimental validation

With several attractive properties, rotary lip seals are widely used in aircraft utility system, and their reliability estimation has drawn more and more attention. This work proposes a reliability estimation approach based on time-varying dependence analysis. The dependence between the two performance indicators of rotary lip seals, namely leakage rate and friction torque, is modeled by time-varying copula function with polynomial to denote the time-varying parameters, and an efficient copula selection approach is utilized to select the optimal copula function. Parameter estimation is carried out based on a Bayesian method and the reliability during the whole lifetime is calculated based on a Monte Carlo method. Degradation test for rotary lip seal is conducted and the proposed model is validated by test data. The optimal copula function and optimal order of polynomial are determined based on test data. Results show that this model is effective in estimating the reliability of rotary lip seals and can achieve a better goodness of fit.     

A global empirical orthogonal function model of plasmaspheric electron content

Based on the method for establishing a global plasmaspheric model using observations from COSMIC and MetOp-A orbit determination GNSS receivers, Chen et al. (2017) obtained a global plasmaspheric total electron content product with a spatial resolution of 2.5° × 5° and a time resolution of 4 h. In this paper, we use those global plasmaspheric electron content product in 2008, 2010, 2011, 2012, 2014 for 1446 days to establish a global plasmaspheric empirical model based on empirical orthogonal function (EOF). The model can well characterize the spatiotemporal variation of plasmaspheric electron content (PEC) and the influence of solar radiation on it. Only the first four orders of EOF sequences can characterize the 98.43% features of the original PEC dataset. The principal component coefficient Pk is decomposed twice during modeling, and the combination of trigonometric function and linear function is used to model Pk to characterize the solar cycle, annual cycle, semi-annual cycle and quarter-cycle variation. We compare the PEC model values with the actual observation data, the results show that the empirical PEC model values are highly correlated with the actual observations. The correlation between the two is above 0.96, and the RMS maximum of the difference between the PEC model values and the observed values are 0.70 TECU, and the average of the difference between the PEC model values and the observed values are −0.18 TECU, respectively. In addition, we validate the reliability of the global plasmaspheric model established by two empirical orthogonal function decomposition method using actual observation data, according to the global distribution of the differences between the PEC model values and the observed values in low solar activity and high solar activity, it can be seen that under low solar activity and high solar activity conditions, the model has good adaptability.     

Estimation of differential code biases with Jason-2/3 onboard GPS observations

With the continuous deployment of Low Earth Orbit (LEO) satellites, the estimation of differential code biases (DCBs) based on GNSS observations from LEO has gained increasing attention. Previous studies on LEO-based DCB estimation are usually using the spherical symmetry ionosphere assumption (SSIA), in which a uniform electron density is assumed in a thick shell. In this study, we propose an approach (named the SHLEO method) to simultaneously estimate the satellite and LEO onboard receiver DCBs by modeling the distribution of the global plasmaspheric total electron content (PTEC) above the satellite orbit with a spherical harmonic (SH) function. Compared to the commonly used SSIA method, the SHLEO model improves the GPS satellite DCB estimation accuracy by 13.46% and the stability by 22.34%, respectively. Compared to the GPS satellite DCBs estimated based on the Jason-3-only observations, the accuracy and monthly stability of the satellite DCBs can be improved by 14.42% and 26.8% when both Jason-2 and Jason-3 onboard observations are jointly processed. Compared with the Jason-2 solutions, the GPS satellite DCB estimates based on the fusion of Jason-2 and Jason-3 observations have an improved consistency of better than 18.26% and 9.71% with the products provided by the Center for Orbit Determination in Europe (CODE) and Chinese Academy of Sciences (CAS). Taking the DCB products provided by the German Aerospace Center (DLR) as references, there is no improvement in accuracy of the GPS satellite DCB estimates based on the fusion of Jason-2 and Jason-3 observations than the Jason-2 solutions alone. A periodic variation is found in the time series of both the Jason-3 and Jason-2 onboard receiver DCB estimates. Preliminary analysis of the PTEC distribution based on the estimated SH coefficients are also presented.     

漂浮基空间机器人捕获卫星过程动力学模拟及捕获后混合体运动的RBF神经网络控制

 讨论了漂浮基空间机器人在轨捕获目标卫星过程的碰撞动力学建模,以及捕获操作结束后空间机器人与卫星混合体的稳定控制问题。首先采用多刚体动力学建模方法并结合空间机器人捕获目标卫星过程中的碰撞动力学特性,建立了漂浮基空间机器人在轨捕获漂浮卫星过程的动力学模型,并在此基础上计算出完成捕获操作后空间机器人与目标卫星混合体关节的运动速度。然后针对卫星及空间机器人系统惯性参数均是未知的复杂情况,应用上述模型、神经网络控制理论和Lyapunov稳定性理论,设计了空间机器人与卫星混合体在捕获过程碰撞冲击影响下稳定运动的高斯径向基函数神经网络控制方案,以达到对捕获卫星的有效控制。此外,高斯径向基函数神经网络控制方案具有不需要测量和反馈载体位置、移动速度与加速度的显著优点。系统数值仿真证实了上述控制方案的有效性。