矢量喷管数学模型研究

采用计算流体力学的有限体积法和神经网络方法,对矢量喷管的统一数学模型进行了研究,并得到了一种以神经网络描述形式的数学模型。该模型为矢量喷管控制规律和带有推力矢量的飞行／推进系统综合控制的研究提供了一定基础。     

Combining frequency and time domain models to forecast space weather

Space weather series incorporate several distinct components, cycles at multiple frequencies, irregular trends, and nonlinear variability. The cycles are stochastic, i.e., the amplitude varies over time. Similarly, the trend is stochastic: the slope and direction of trending change repeatedly. This study sets out a combined model using both frequency and time domain methods, in two stages. In the first stage, a frequency domain algorithm is estimated and forecasted. In the second stage, the forecast is used as an input in a neural network. The combined model also includes a term enabling the model to react inversely to large deviations between the actual values and forecast. The models are evaluated using two data sets, the hemispheric power data obtained from the Polar Orbiting Environment satellites, and the Aa geomagnetic index. All the series are at a daily resolution. Forecasting experiments are run over horizons of 1–7 days. The models are estimated using a moving window or adaptive approach. The combined model consistently achieves the most accurate results. Among single equation methods, the frequency domain model is more accurate for the geomagnetic index because it is able to capture the underlying cycles more effectively. In the hemispheric power series, the cycles are less pronounced, so that time domain methods are more accurate, except at very short horizons. Nevertheless, in both data sets, the combined model works well because the frequency domain algorithm captures cyclical behavior, while the neural net is better able to capture short-term dependence and trending.     

Comparison of topside ionosphere scale height modeled by the Topside Sounder Model and incoherent scatter radar ionospheric model

The topside ionosphere scale height extracted from two empirical models are compared in the paper. The Topside Sounder Model (TSM) provides directly the scale height (H_T), while the incoherent scatter radar ionospheric model (ISRIM) provides electron density profiles and its scale height (H_R) is determined by the lowest gradient in the topside part of the profile. H_T and H_R are presented for 7 ISR locations along with their dependences on season, local time, solar flux F10.7, and geomagnetic index ap. Comparison reveals that H_T values are systematically lower than respective H_R values as the average offset for all 7 stations is 55 km. For the midlatitude stations Arecibo, Shigaraki, and Millstone Hill this difference is reduced to 43 km. The range of variations of H_R is much larger than that of H_T, as the H_T range overlaps the lower part of the H_R range. Dependences on ap, DoY and LT are much stronger in the ISRIM than in TSM. This results in much larger values of H_R at higher ap. Diurnal amplitude of H_R is much larger than that of H_T, with large maximum of H_R at night. The present comparison yields the conclusion that the ISR measurements provide steeper topside Ne profiles than that provided by the topside sounders.     

基于三类非线性函数的认证码的构造

为了将高度非线性函数应用于认证码构造理论．讨论了非线性函数的度量，给出了由三类非线性函数构造的Cartesian认证码，并且当编码规则按等概率分布选取时，分别计算了三类认证码的模仿攻击和欺骗攻击成功的概率。结果表明，第二类认证码模仿攻击成功的概率达到了下界。在n取值相同的条件下，第一类认证方案模仿攻击成功的概率比第三类的大。     

Neal-Smith时域PIO预测准则及应用

基于Neal-Smith频域准则,Neal-Smith时域准则(TDNS, Time Domain Neal-Smith criterion)是另一重要的固定翼飞机驾驶员诱发振荡(简称PIO)预测准则,其无需对人机系统的非线性进行任何假设和简化.以某机型为模型,采用TDNS,通过俯仰角闭环操纵误差信号与目标捕获时间之间的关系来同时预测I、II型驾驶员诱发振荡,同时分析了不同速率限制环节对预测结果的影响,基于误差信号的均方差及其二次偏导数,得到了TDNS准则一般计算方法及各个影响因素的关系.结果表明,TDNS准则的计算方法可行、直观、高效.     

采用丝杠传动的电动舵机运动学分析

为了改善旋转电动舵机的控制输出中存在的系统振荡问题,针对电动舵机中连杆及摇臂等传动结构导致的非线性不确定特性,文章通过建立传动机构的数学模型,根据其位置变化量及速度变化量关系,确立了控制输出与实际输出在传动过程中的正逆运动学方程,分析了传动机构运动时所引入的非线性环节,并提出了通过修正传动参数来补偿非线性的影响,为伺服系统的分析及控制器设计提供参考,对提高舵机系统的控制性能与控制精度有重要作用。     

基于多小波的Volterra级数非定常气动力建模方法

非定常气动力建模除了要准确描述气动力的非定常特性,还要反映其非线性特性。Volterra级数因为对系统非线性具有很强的描述能力正日益受到重视。一阶Volterra核只能表达线性特性,要建立反映非线性特性的非定常气动力模型,需要引入二阶核甚至更高阶核的影响。高阶Volterra核辨识的主要困难在于待辨识参数的数量随着核阶次的增加而呈指数增加导致计算难度急剧加大,即出现所谓维数灾难问题。以一种分段二次多小波为基函数将Volterra核展开,求解一个高维病态方程组来计算展开系数,利用小波的多分辨分析在时间和频率两个维度的分解特性将方程降维,最终将问题转化为求解一个低维方程组得到稳定解。通过NACA0012翼型在马赫数0.8下作沉浮运动时,升力系数、阻力系数和俯仰力矩系数的二阶核和三阶核的辨识构建非定常气动力模型,然后由此计算不同减缩频率下的气动力并与CFD结果进行比较,验证了Volterra级数对非线性非定常气动力的描述能力和多小波处理方法的有效性。     

STUDY ON IRONING USING UPPER-BOUND APPROACH

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