重特征值模态灵敏度分析的非线性摄动法

利用非线性摄动等式,推导了实对称矩阵的重特征值模态灵敏度计算公式。该方法的优点是保持了原特征系统矩阵的对称性和带宽。数值算例表明该方法精度高,易于计算和实施。     

An innovative navigation scheme of powered descent phase for Mars pinpoint landing

Pinpoint landing (within 100 m from the target) is essential for future Mars exploration missions. This paper deals with one aspect of the pinpoint landing architecture—the navigation performance improvement during the powered descent phase, and proposes an innovative navigation scheme to obtain the vehicle complete and accurate states. On the basis of dead reckoning relying on the Inertial Measurement Unit, measurements of the Integrated Doppler Radar are adopted to correct the vehicle velocity and altitude. Distance between the vehicle and one Mars Orbiter as well as their line-of-sight relative velocity is measured by a radio sensor, and integrated in the filter to correct the vehicle horizontal position. The innovative navigation system is based on an Extend Kalman Filter. Two observation schemes are developed. One considers measurements of the Integrated Doppler Radar and radio range measurement. Another further considers radio velocity measurement. The performance of the innovative navigation scheme is greatly influenced by the position of the Mars Orbiter with respect to the target. Stochastic analyses are performed to obtain optimal locations of Mars Orbiter. Finally, the innovative navigation scheme performances are assessed through stochastic simulations. Its performance improvements are demonstrated by comparison with the Integrated Doppler Radar only navigation scheme.     

复杂网络的灰点及灰度分析(英文)

依据对复杂网络和灰色系统理论的相关分析,提出了复杂网络中的灰点问题,认为灰点分为存在而未知的灰点和演化灰点两类,并给出了相关定义。进一步给出复杂网络灰度问题的相关描述,将网络灰度分为相对灰度和绝对灰度,并分别进行了证明。     

基于多活性代理的多星测控调度方法

多星测控调度问题是一个具有多时间窗口、多资源约束的优化问题,其中多星测控任务调度的建模和求解算法是关键。在多活性代理理论的基础上,引入任务调度活性度概念及多活性代理活性保持的协调协商机制,建立基于活性度的多星测控调度模型,并给出一种多活性代理协调协商遗传算法。最后给出实验示例对所提出的算法进行仿真验证。仿真实验表明,所提出的基于多活性代理协商协调的模型及算法能够更好地解决多星测控任务调度问题。     

激光辐照条件下光电电池温度特性的实验研究

激光输能具有广阔应用前景,而光电电池是激光输能技术中实现光-电转换的核心部件。文章围绕温度对光电电池输出性能的影响,通过建立电池输出性能实验测试系统,研究了一定激光功率密度下砷化镓电池和硅电池在不同温度下的伏安特性,以及开路电压、短路电流、最大输出功率、匹配负载、转换效率、填充因子随电池温度的变化规律,并给出其定量表达式,可为激光输能条件下光电电池的选择以及光电电池温度特性预测提供参考。     

用参数辨识法进行直升机悬停性能拓展

准确计算直升机在不同飞行状态的有效气动参数对于确定直升机飞行性能具有重要意义。然而,由于复杂的旋翼空气动力现象以及直升机状态和环境条件的变化,准确预估气动参数有较大难度。为此,采用无量纲分析法建立直升机悬停状态的数学模型,首先对参数重组,确定了几个悬停状态重要参数,包括气动参数和直升机状态参数;然后,以直-9×型直升机为例,结合实际试飞数据,提出了用最小二乘法对该模型进行参数辨识的方法;最后,通过相关性分析,确定了辨识方法的可行性,并将辨识结果有效地用于直升机悬停性能拓展。结果表明,这种利用参数辨识进行性能拓展的方法是可行的,由于辨识结果是利用实际试飞数据确定的,拓展结果具有较高的可信度。这种数据处理方法可有效减少试飞周期,节约试验成本。     

基于UKF的微小卫星姿态确定方法研究

围绕某日-地空间环境组网探测系统中三轴稳定微小卫星定姿分系统的设计需求,基于陀螺、太阳敏感器、磁强计和星敏感器4种敏感器,研究了微小卫星在速率阻尼模式、太阳捕获模式、对日对地定向及维持模式、试验模式下的系统建模方法,以及基于Unscented卡尔曼滤波(UKF)的组合定姿方法。数值仿真结果表明,本文定姿方法的姿态确定精度满足该系统中三轴稳定微小卫星在轨运行的定姿精度要求,为该微小卫星半物理仿真系统的研究及其在轨运行时的姿态确定提供了依据。     

双密封结构的泄漏理论及其应用研究

建立了双密封结构系统的数学模型 ,通过理论分析和数值计算 ,揭示了双密封结构系统正压泄漏的漏率、漏量与泄漏时间关系的规律及其影响因素的结论。这些研究结果可用于双密封结构系统的设计、检漏和泄漏安全评估 ,以理论指导实践。     

控制力矩陀螺框架高精度周期随动控制

为实现控制力矩陀螺框架伺服系统的高精度周期随动控制,采用比例积分微分(PID,Proportion Integration Differentiation)控制器结合重复控制器的控制方式,PID控制器实现框架伺服系统静态和匀速运动的高精度控制,插入式重复控制器实现对周期性输入信号的精确跟踪.对控制力矩陀螺框架系统进行了建模,设计了PID控制器与插入式重复控制器,并分析了重复控制器的稳定性条件、稳态跟踪性能和对扰动的抑制能力.仿真结果和实验结果表明:采用插入式重复控制器使控制力矩陀螺跟踪1Hz给定速度信号时的稳态跟踪误差大幅减少.PID控制器结合插入式重复控制器结构简单,两者可分开独立设计,参数设计容易.     

Application of support vector machine combined with K-nearest neighbors in solar flare and solar proton events forecasting

The support vector machine (SVM) combined with K-nearest neighbors (KNN), called the SVM-KNN method, is new classing algorithm that take the advantages of the SVM and KNN. This method is applied to the forecasting models for solar flares and proton events. For the solar flare forecasting model, the sunspot area, the sunspot magnetic class, and the McIntosh class of sunspot group and 10 cm solar radio flux are chosen as inputs; for the solar proton event forecasting model, the inputs include the longitude of active regions, the flux of soft X-ray, and those for the solar flare forecasting model. Detailed tests are implemented for both of the proposed forecasting models, in which the SVM-KNN and the SVM methods are compared. The testing results demonstrate that the SVM-KNN method provide a higher forecasting accuracy in contrast to the SVM. It also gives an increased rate of ‘Low’ prediction at the same time. The ‘Low’ prediction means occurrence of solar flares or proton events with predictions of non-occurrence. This method show promise for forecasting models of solar flare and proton events.