Double-stage Metamodel and Its Application in Aerodynamic Design Optimization

Constructing metamodel with global high-fidelity in design space is significant in engineering design. In this paper, a double-stage metamodel (DSM) which integrates advantages of both interpolation metamodel and regression metamodel is constructed. It takes regression model as the first stage to fit overall distribution of the original model, and then interpolation model of regression model approximation error is used as the second stage to improve accuracy. Under the same conditions and with the same samples, DSM expresses higher fidelity and represents physical characteristics of original model better. Besides, in order to validate DSM characteristics, three examples including Ackley function, airfoil aerodynamic analysis and wing aerody-namic analysis are investigated. In the end, airfoil and wing aerodynamic design optimizations using genetic algorithm are presented to verify the engineering applicability of DSM.     

Study of ADS-B Data Evaluation

In western China, the terrain and meteorological conditions are so complex that it is not suitable to construct new radar stations. Automatic dependent surveillance-broadcast (ADS-B) is a totally new surveillance method, so before practically applied and operated in China, abundant tests and evaluations are necessary to validate the performance of ADS-B and guarantee the operational security. During the flight tests, we collect the data of radar, ADS-B and high accuracy position and compare the performance of ADS-B with radar based on high accuracy position. To solve the asynchronous problem among radar data, ADS-B data and real-time kinematic (RTK) data caused by different update rates, this article proposes the technique of synchronizing multi-surveillance data by extrapolating from the data of low update rate to high update rate according to velocity and heading. Meanwhile, because radar data, ADS-B data and RTK data are expressed in different coordinates and cannot be compared each other, this article provides a method to unifying the coordinates of multi-surveillance data. By the analysis and evaluation, we can conclude that the performance of ADS-B is better than radar.     

低利用率下民机结构维修间隔确定模型

制定民用飞机结构维修大纲的核心内容之一是确定结构维修间隔,现有的分析模型普遍没有综合考虑民机利用率对维修间隔各指标的影响。以民机在环境损伤下的金属结构维修间隔为研究背景,综合考虑利用率对确定结构维修间隔各个指标的影响,应用K-means算法和AHP （Analytic Hierarchy Process）-熵值法,建立了一种某型国产民机低利用率下金属结构环境损伤维修间隔的确定模型,并通过选取相似机型的典型结构进行了实例验证。分析结果表明：所建模型与飞机利用率匹配关系良好,符合工程实际,在一定程度上解决了国产民机制定维修大纲的过程中,由于缺少运营数据和维修数据而导致维修间隔的确定偏于主观的问题。     

一种地空3D-Massive MIMO信道模型

为了研究地空3D-Massive MIMO系统信道特性,提出一种基于三维单跳同心圆环散射体的地空3D-Massive MIMO信道模型。相比传统地空3D MIMO信道模型有两方面改进,首先是建立了基于单跳圆环散射体3D几何精确位置关系的球面波天线阵元相位偏移模型,其次采用生灭过程对Massive MIMO阵列上的非平稳特性进行建模。推导了该模型的信道统计特征函数,通过对特征函数理论推导值与蒙特卡洛统计值进行仿真对比,验证了理论推导正确性。此外,对所提信道模型与基于平面波的传统地空3D MIMO信道模型的空间相关性进行了分析及仿真对比,结果表明:在远场环境下,两者基本一致;在近场环境下,传统平面波模型不再适用,两者存在差异。最后,对若干组表征信道特征的仿真结果与公开文献中地空信道实际测试数据进行对比分析。表明本模型作为普遍适用性模型,可以根据信道的测试条件、测试环境和测试结果来优化参数配置以趋近于实际信道,以对特定信道进行精确建模。     

基于多智能体混合学习的多星协同动态任务规划算法(英文)

针对多星协同动态任务规划问题,以往多采用基于启发式的重规划算法,但是由于启发式策略依赖于具体任务,使得优化性受到影响。注意到协同规划的历史信息对后续协同规划的影响,本文提出了一种基于策略迭代的多智能体强化学习和迁移学习的混合学习算法求解该问题近似最优策略。本文的多智能体强化学习方法利用神经网络描述各颗卫星的强化学习策略,通过协同进化的方法迭代搜索具有最优拓扑结构和连接权重的策略神经网络个体。针对随机出现的观测任务请求导致历史学习策略失效,通过迁移学习将历史学习策略转换为当前初始策略,保证规划质量前提下加快多星协同任务规划速度。仿真实验及分析结果表明本文算法对动态随机出现的任务请求有良好的适应性。     

A New Probabilistic Transformation in Generalized Power Space

The mapping from the belief to the probability domain is a controversial issue, whose original purpose is to make (hard) decision, but for contrariwise to erroneous widespread idea/claim, this is not the only interest for using such mappings nowadays. Actually the probabilistic transformations of belief mass assignments are very useful in modern multitarget multisensor tracking systems where one deals with soft decisions, especially when precise belief structures are not always available due to the existence of uncertainty in human being's subjective judgments. Therefore, a new probabilistic transformation of interval-valued belief structure is put forward in the generalized power space, in order to build a subjective probability measure from any basic belief assignment defined on any model of the frame of discernment. Several examples are given to show how the new transformation works and we compare it to the main existing transformations proposed in the literature so far. Results are provided to illustrate the rationality and efficiency of this new proposed method making the decision problem simpler.     

Static Analysis of Functionally Graded Sandwich Plates Using an Efficient and Simple Refined Theory

In this paper, a new displacement based high-order shear deformation theory is introduced for the static response of function-ally graded sandwich plate. Unlike any other theory, the number of unknown functions involved is only four, as against five in case of other shear deformation theories. The theory presented is variationally consistent, has strong similarity with classical plate theory in many aspects, does not require shear correction factor, and gives rise to transverse shear stress variation such that the transverse shear stresses vary parabolically across the thickness satisfying shear stress free surface conditions. Two common types of functionally graded sandwich plates, namely, the sandwich with functionally graded facesheet and homogeneous core and the sandwich with homogeneous facesheet and functionally graded core, are considered. Governing equations are derived from the principle of virtual displacements. The closed-form solution of a simply supported rectangular plate subjected to sinu-soidal loading has been obtained by using the Navier method. The validity of the present theory is investigated by comparing some of the present results with those of the classical, the first-order and the other higher-order theories. It can be concluded that the proposed theory is accurate and simple in solving the static bending behavior of functionally graded sandwich plates.     

Regularized Robust Filter for Spacecraft Attitude Determination

A modified regularized robust filter is proposed for spacecraft attitude determination in the presence of relative misalignment of attitude sensors. The filter is designed to minimize the worst-possible residual norm on condition that there is parametric uncertainty in the measurement model. The weighting matrix of the residual norm is designed to minimize the upper bound of the estimation error variance. The performance of the proposed attitude determination robust filter is illustrated with the use of real test data from a real three-floated gyroscope. Simulation results demonstrate that the attitude estimation accuracy is improved by using the proposed algorithm.     

多渐消因子Kalman滤波器在SINS初始对准中的应用(英文)

针对系统模型和统计信息不能精确已知的条件下Kalman滤波无法给出最优解这一问题,单一渐消因子Kalman滤波算法对于简单的系统是有效的,但是对于复杂的多变量系统,仅仅利用单个的渐消因子是不够的。本文提出了一种多渐消因子滤波算法,通过利用开窗法计算新息序列协方差的无偏估计获得渐消因子矩阵。利用渐消因子矩阵调节一步预测均方误差矩阵k|k1P,对不同的滤波通道提供不同的渐消速率。将该方法应用于SINS的初始对准中,仿真和试验结果表明:当真实系统噪声统计特性同设定参数不一致时,对准精度明显高于其他滤波算法。其对不确定性噪声具有较低的敏感度,对系统参数具有较好的滤波效果。因而,在实际应用中具有重要的参考价值。     

多电飞机作动系统的体系结构优化(英文)

多电技术的深入发展使得飞机上可选择的功率源和作动器种类越来越多,这导致在机载作动系统体系结构优化设计过程中出现了不同功率源和作动器组合的极端复杂性,传统的"试凑"法已无法完成设计任务。首先介绍了多电飞机飞控作动系统(Flight Control Actuation System,FCAS)的组成,计算了其可能的体系结构数量;其次提出了FCAS体系结构在安全性、重量和效率方面的评价指标,计算了全机各舵面均采用同类作动器时的评价指标值;最后对比分析了现有的各种多目标优化算法,采用遗传算法给出了多电飞机FCAS体系结构的多目标优化设计结果。对比传统的只采用阀控液压伺服作动器的作动系统体系结构,优化后的体系结构可以在满足安全可靠性要求的前提下使系统的重量减轻6%左右,效率提高30%左右。