转子系统模态理论的特点和应用

本文从无阻尼系统出发,理论上分析了转子系统振动方程的特征根,特征向量所具有的特点。除讨论正交性外,还进行了模态空间完备性的分析,推出转子系统强迫振动响应的解析表达式和传递函数的表达式,为参数辨识提供了理论依据。     

小卫星动平衡研究--质心不对中对姿态的影响

首先定性分析质心不对中对星体动力学特性的影响，然后由拉格朗日第二类方程导出引力场下星体运动方程的矩阵表达式，最后以50kg级长方体3轴稳定小卫星为例，分析不同初角速度和不同时间历程情况下质心不对中对星体运动姿态的影响，并分析其对星体运动稳定性的影响．本文研究为同类品种小卫星的构型设计、姿态控制系统设计以及制定卫星动平衡精度提供依据。     

Forecasting magnetopause crossing locations by using Neural Networks

Given the highly complex and nonlinear nature of Near Earth Space processes, mathematical modeling of these processes is usually difficult or impossible. In such cases, modeling methods involving Artificial Intelligence may be employed. We demonstrate that data driven models, such as the Neural Network based approach, shows promise in its ability to forecast or predict the behavior of these processes. In this paper, modeling studies for forecasting magnetopause crossing locations are summarized and a Neural Network algorithm is presented to describe the nonlinear time-dependent response of the subsolar region of the magnetopause to varying solar wind conditions. In our approach the past history of the solar wind has, for the first time to the best knowledge of the authors, been included in forecasting the subsolar region of the magnetopause. It is proposed that the data driven approach is a valid approach to understanding and modeling the physical phenomena of Near Earth Space. The only basic requirement for the data driven approach is the availability of representative data for the phenomena. The objective of this paper is to demonstrate that by using WIND and GEOTAIL satellite data a Neural Network based model can be adapted to the modeling of the Earth’s magnetopause.     

谱载下基于模糊Miner法则的疲劳寿命估算

在载荷谱中,当疲劳应力稍低于疲劳极限时,对构件是否造成损伤呈现出某种"模糊"过渡状态.运用模糊数学的隶属函数,建立了考虑"模糊"损伤状态的Miner法则.按照常规Miner法则和模糊Miner法则,分别给出了程序块谱作用下疲劳寿命的估算公式.实例估算与试验结果的对比表明:采用模糊Miner法则,可使疲劳寿命的估算误差减少18.33%.     

直线度误差目标函数凸凹性的研究

证明了直线度误差最小区域评定法的目标函数是一维欧式空间R1中的连续、不可微的凸函数 ,从而证明了目标函数的全局极小值是唯一的。     

中继卫星系统地面云存储架构设计

针对中继卫星系统日益增长的海量数据存储需求,探索将云技术应用于中继卫星地面存储系统中,研究并设计了适用于中继卫星系统的分布式云存储的体系架构.该架构通过分布式存储和存储虚拟化技术,对存储资源进行了整合,将分布在不同地理位置上的存储网络,集合成一个大规模广域云存储系统,可提供整体存储和访问的功能,并实现对数据的高效“存”、“取”、“管”.与传统NAS(Network Attached Storage,网络附加存储)架构分析比较,该架构从系统扩展性、可靠性和服务性等多个方面均更加具有优势,能够适应日益增长的中继卫星系统海量数据存储需求,解决中继卫星系统中大容量数据存储的瓶颈.     

Energy-optimal reconfiguration of satellite formation flying in the presence of uncertainties

In this study, a two-step control methodology is developed for energy-optimal reconfiguration of satellites in formation in the presence of uncertainties or external disturbances. First, based on a linear deterministic system model, an optimal control law is analytically determined such that a satellite maneuvers from an initial state to a final state relative to another satellite. The structure of this optimal solution is predetermined and simply given by a linear combination of the fundamental matrix solutions associated with the original equations of relative motion. Only the coefficients are to be determined to satisfy given initial and final conditions. In the second step, an uncertain nonlinear formation system is considered and a robust adaptive controller is designed to compensate for the effects of uncertainties or disturbances that the formation system may encounter. Although the control strategy is inspired by sliding mode control, it produces smooth control signals, thereby avoiding chattering. Also, an adaptation law is added such that the uncertainty or disturbance effects are effectively and quickly eliminated without a priori information about them. The combination of these two controllers guarantees that the satellite accurately tracks the optimal path in the unknown environment. Numerical simulations demonstrate the effectiveness and accuracy of the proposed two-step control methodology, in which a satellite formation is optimally reconfigured under unknown environmental disturbances.     

Structural dynamic responses of a stripped solar sail subjected to solar radiation pressure

The stripped solar sail whose membrane is divided into separate narrow membrane strips is believed to have the best structural efficiency. In this paper, the stripped solar sail structure is regarded as an assembly made by connecting a number of boom-strip components in sequence. Considering the coupling effects between booms and membrane strips, an exact and semi-analytical method to calculate structural dynamic responses of the stripped solar sail subjected to solar radiation pressure is established. The case study of a 100 m stripped solar sail shows that the stripped architecture helps to reduce the static deflections and amplitudes of the steady-state dynamic response. Larger prestress of the membrane strips will decrease stiffness of the sail and increase amplitudes of the steady-state dynamic response. Increasing thickness of the boom will benefit to stability of the sail and reduce the resonant amplitudes. This proposed semi-analytical method provides an efficient analysis tool for structure design and attitude control of the stripped solar sail.     

An update global model of hmF2 from values estimated from ionosonde and COSMIC/FORMOSAT-3 radio occultation

In this paper, we present our recent work on developing an updated global model of the ionospheric F2 peak height hmF2 parameter by combining data from the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC/FORMOSAT-3) radio occultation (RO) measurements and from the extended global ionosonde stations. In particular, 10 Chinese ionosonde stations’ data are newly introduced into this study. The modeling technique used is based on a two-layer empirical orthogonal function (EOF) expansion. Global distributions of hmF2 maps calculated using the newly constructed global model and the one provided by the International Reference Ionosphere model (IRI-ITU-R) are compared with the global distributions of hmF2 obtained by the COSMIC RO measurements and quantitative statistical analysis of the differences between the model results and those of the COSMIC RO measurements is made for the low (2008) and high (2012) solar activity years. The obtained average root-mean-square differences (RMSEs) for our model are 27.7 km (11.1%) and 31.0 km (9.8%), respectively for the years 2008 and 2012, whereas those for the IRI-ITU-R model are 39.9 km (16.9%) and 35.0 km (11.6%), respectively. Comparison of the results calculated both by our model and the IRI-ITU-R model with the digisonde observation is also made. The comparisons show that the newly constructed global hmF2 model can reproduce reasonably well the observations and perform better than IRI-ITU-R model.     

Prediction of ionospheric total electron content using adaptive neural network with in-situ learning algorithm

The Ionospheric Total Electron Content is responsible for the group delay of the signals from the Navigation satellites. This delay causes ranging error, which in turn degrades the accuracy of position estimated by the receivers. For critical applications, single frequency receivers resort to Satellite Based Augmentation Systems in order to have improved accuracy and integrity. The performance of these systems in terms of accuracy can be improved if predictions of the delays are available simultaneously with real measurements. This paper attempts to predict the Total Electron Content using adaptive recurrent Neural Network at three different locations of India. These locations are selected at the magnetic equator, at the equatorial anomaly crest and outside the anomaly range, respectively. In-situ Learning Algorithm has been used for tracking the non-stationary nature of the variation. Prediction is done for different prediction intervals. It is observed that, for each case, the mean and root mean square values of prediction errors remain small enough for all practical applications. Analysis of Variance is also done on the results.