一种飞-续-飞随机谱的编制方法及软件

本文介绍了一种飞-续-飞随机谱的编制方法和软件。它以空测的重心过载数据为基础,经过数据处理后,建立对应于每个飞行任务的Markov矩阵。并调整统计平均后的Markov矩阵以保证可得到一个不中断的过载序列。然后从矩阵中抽取半循环序列,构成飞-续-飞随机谱。本文中讨论了矩阵中半循环的随机抽取方法,给出了应用实例。     

基于PSO的船体动态变形模型参数在线辨识

在船体变形测量领域,惯性量匹配法凭借其高精度、易实现的优点成为了时下的研究热点。详细介绍了角速度匹配法进行船体变形角估计的原理,针对算法中动态变形模型（二阶Markov）参数难以确定的问题,推导了两套INS的角增量输出差值与动态变形角之间的关系,建立了利用角增量差值的自相关函数进行求参的理论依据。在求参工具上选择了粒子群算法,借助指数衰减正弦信号的形式建立算法模型,并且合理设置算法参数,最终形成一套完整的在线辨识方案。仿真实验证实,该方案能够实现动态变形模型参数的精确辨识,辨识精度较高,且SNR门限低。最终的变形角估计结果表明,结合该参数辨识算法,船体变形角估计误差可控制在10″左右,证明了该方法的可行性。     

马尔可夫分析在系统安全性评估中的应用研究

安全性分析是适航符合性验证的重要方法。对马尔可夫分析在系统安全性评估中的应用进行了深入研究,阐明了马尔可夫分析的作用与应用时机,结合功能危险状态“V1速度后起落架无指令收起”分别给出了在初步系统安全性评估与系统安全性评估中进行马尔可夫分析的一般方法,将马尔可夫分析与故障树分析的结论进行了对比,袁明了本文方法的适用性。     

New findings and appraisal of structural control on polygonal impact crater rim-geometry,a study from Mare Fecunditatis,Moon

Polygonal Impact Craters (PICs), having a distinct polygonal rim geometry, are common on terrestrial planets, their natural satellites such as Earth’s Moon and the asteroids. The straight segments of PIC-rims are arguably subparallel or oblique to existing fracture/fault planes in their vicinity, and such pre-existing structural weak planes are considered responsible for the shape of the PICs. The Mare Fecunditatis, a lunar maria, preserves mappable PICs as well as different geomorphic features like wrinkle ridges, grabens and pit crater chains which owe their origin to either compressional or extensional faulting. To understand the structural control, if any, on the PIC-rim geometry in Mare Fecunditatis, PICs, both simple and complex, and the deformational features are mapped, superposition relations between them are observed and trends are compared. The comparison between frequency of rim segment trends of the two types of PICs with wrinkle ridges, grabens and pit crater chains, and also statistical correlation between them, interestingly indicate that the wrinkle ridges and grabens are found to have negligible or no influence on the rim geometry of the PICs. Wrinkle ridges, known to be a group of the Mare Fecunditatis' oldest deformation features, are older than most of the preserved craters and are likely to have had control over the PIC shape. However, lack of correlation between the trends of wrinkle ridges and PIC rims indicates that most of the craters were formed after the fractures beneath the old wrinkle ridges ceased to act as mechanical discontinuity planes due to possible induration caused by fracture-filling through concomitant and later magma injection. The PICs dispersed throughout the maria could have avoided the influence of the grabens, the majority of which are located near the margin of the maria. Pit crater chains with possible deep roots and still/recently continued dike activities, were the only available weak planes which could influence the PIC rim shapes.     

Supervised learning with probability interpretation in airfoil transition judgment

Transition prediction has always been a frontier issue in the field of aerodynamics. A supervised learning model with probability interpretation for transition judgment based on experimental data was developed in this paper. It solved the shortcomings of the point detection method in the experiment, that which was often only one transition point could be obtained, and comparison of multi-point data was necessary. First, the Variable-Interval Time Average (VITA) method was used to transform the fluctuating pressure signal measured on the airfoil surface into a sequence of states which was described by Markov chain model. Second, a feature vector consisting of one-step transition matrix and its stationary distribution was extracted. Then, the Hidden Markov Model (HMM) was used to pre-classify the feature vectors marked using the traditional Root Mean Square (RMS) criteria. Finally, a classification model with probability interpretation was established, and the cross-validation method was used for model validation. The research results show that the developed model is effective and reliable, and it has strong Reynolds number generalization ability. The developed model was theoretically analyzed in depth, and the effect of parameters on the model was studied in detail. Compared with the traditional RMS criterion, a reasonable transition zone can be obtained using the developed classification model. In addition, the developed model does not require comparison of multi-point data. The developed supervised learning model provides new ideas for the transition detection in flight experiments and other experiments.     

拦截大气层内机动目标的深度强化学习制导律

针对大气层内高速机动目标的拦截问题，提出了一种基于双延迟深度确定性策略梯度(TD3)算法的深度强化学习制导律，它直接将交战状态信息映射为拦截弹的指令加速度，是一种端到端、无模型的制导策略。首先，将攻防双方的交战运动学模型描述为适用于深度强化学习算法的马尔科夫决策过程，之后通过合理地设计算法训练所需的交战场景、动作空间、状态空间和网络结构，并引入奖励函数整形和状态随机初始化，构建了完整的深度强化学习制导算法。仿真结果表明：与比例导引和增强比例导引两种方案相比，深度强化学习制导策略在脱靶量更小的同时能够降低对中制导精度的要求；具有良好的鲁棒性和泛化能力，并且计算负担较小,具备在弹载计算机上运行的条件。     

一种面向空天飞机再入的智能自适应复合控制方法

针对空天飞机再入横、侧向通道的姿态控制问题，设计了一种智能神经网络自适应复合控制方法，基于误差反馈学习准则在线更新神经网络权重以补偿全量姿态控制律输出的姿态控制指令。同时，面向再入过程横侧通道的强耦合问题，引入了耦合控制系数，以降低横、侧通道间的控制干扰。此外，提出了一种自适应链式控制分配律，在控制信号中引入正交优化多正弦激励，基于递推最小二乘方法对气动参数进行在线辨识，进而实时更新链式分配策略。最后，对空天飞机再入横侧向通道的神经网络自适应复合控制方法进行数学仿真校验，验证了该方法的有效性和鲁棒性。