基于无奇点根数的空间相对导航插值滤波算法

为了提高椭圆轨道航天器的相对导航精度,将基于Stirling公式的多项式插值滤波方法（DDF2）引入导航算法,降低了传统的卡尔曼滤波方法中泰勒级数展开线性化     

Polynomial networks based adaptive attitude tracking control for NSVs with input constraints and stochastic noises

This paper proposes a backstepping technique and Multi-dimensional Taylor Polynomial Networks (MTPN) based adaptive attitude tracking control strategy for Near Space Vehicles (NSVs) subjected to input constraints and stochastic input noises. Firstly, considering the control input has stochastic noises, and the attitude motion dynamical model of the NSVs is actually modeled as the Multi-Input Multi-Output (MIMO) stochastic nonlinear system form. Furthermore, the MTPN is used to estimate the unknown system uncertainties, and an auxiliary system is designed to compensate the influence of the saturation control input. Then, by using backstepping method and the output of the auxiliary system, a MTPN-based robust adaptive attitude control approach is proposed for the NSVs with saturation input nonlinearity, stochastic input noises, and system uncertainties. Stochastic Lyapunov stability theory is utilized to analysis the stability in the sense of probability of the entire closed-loop system. Additionally, by selecting appropriate parameters, the tracking errors will converge to a small neighborhood with a tunable radius. Finally, the numerical simulation results of the NSVs attitude motion show the satisfactory flight control performance under the proposed tracking control strategy.     

基于多项式拟合SDRE的三维导引律设计

应用多项式拟合的SDRE方法结合改进的极坐标系(MPC)设计了三维次优导引律。介绍了 SDRE方法与多项式拟合的SDRE方法,后者是前者十分优越的逼近;推导了MPC下的弹目相对 运动方程,将球坐标下的六个状态方程减少到了三个并且满足多项式拟合SDRE方法的应用前 提;在此基础上,推导出了三维拟合SDRE导引律(nSDRE)。仿真显示,nSDRE是一种有效的导 引律,较广义理想比例导引律(GIPN)具有更好的导引品质,特别在目标机动时,nSDRE能更 好地应对目标机动引起的视线转率发散而导致脱靶的问题。
     

确定自旋航天器旋转轴的动平衡方法

本文研究自旋航天器的旋转轴的试验测定方法，给出自旋轴方向的表示方法及其与转动惯量，惯性积的关系，建立了利用动平衡试验的不平衡量确定自旋轴相对平衡旋转轴偏差的计算机公式，从而可以利用动平衡试验的测试结果确定自自旋轴的方向，文末的例中讨论了动平衡机的最小可达剩余不平衡量对试验结果的影响。     

Variable structure multiple model fixed-interval smoothing

This paper focuses on fixed-interval smoothing for stochastic hybrid systems. When the truth-mode mismatch is encountered, existing smoothing methods based on fixed structure of model-set have significant performance degradation and are inapplicable. We develop a fixed-interval smoothing method based on forward- and backward-filtering in the Variable Structure Multiple Model (VSMM) framework in this paper. We propose to use the Simplified Equivalent model Interacting Multiple Model (SEIMM) in the forward and the backward filters to handle the difficulty of different mode-sets used in both filters, and design a re-filtering procedure in the model-switching stage to enhance the estimation performance. To improve the computational efficiency, we make the basic model-set adaptive by the Likely-Model Set (LMS) algorithm. It turns out that the smoothing performance is further improved by the LMS due to less competition among models. Simulation results are provided to demonstrate the better performance and the computational efficiency of our proposed smoothing algorithms.     

叶顶间隙偏差对叶片气动性能影响的不确定性研究

在压气机叶片加工过程中，实际加工得到的叶片外形与设计叶型不可避免会存在一些偏差。为研究叶片叶顶间隙尺寸波动对性能的影响，以Rotor37为研究对象，采用三维定常数值模拟方法，基于非嵌入式混沌多项式中二维正态分布变量产生方法，分别对叶片前缘叶顶间隙和尾缘叶顶间隙进行尺寸波动干扰，研究了叶顶间隙不确定性对气动性能和流场的不确定性影响，评估了公差带内叶顶间隙偏差与气动性能变化的相关性，并探究了叶顶间隙变化对叶片稳定裕度的影响机理。研究发现，叶顶间隙偏差对等背压条件下叶片质量流量、等熵效率和总压比的平均水平几乎不会造成影响；叶顶间隙偏差所造成的气动性能分布标准差随工况点向不稳定边界的逼近而逐渐增大。同时，叶顶间隙不确定性会导致样本稳定裕度均值有所降低，不确定性分析中稳定裕度均值相对原型叶片下降了2.42%。流场结构方面，叶顶间隙偏差主要影响80%叶高以上部分流场；叶顶间隙偏差对叶顶区域泄漏流产生的影响，导致了叶片稳定裕度的变化。