基于有向图的蜂群无人机故障影响

基于蜂群无人机控制模型，针对虚假数据注入的故障情形，为了分析该故障情形下，蜂群无人机中故障的的影响及传播关系，采用故障传播有向图及一致性理论，开展蜂群无人机故障影响机理研究。首先，通过Dijkstra算法计算故障源到各无人机的最短路径，建立故障传播有向图；然后预测各无人机受故障影响的程度，结合蜂群无人机系统，计算一致性行为偏差的指标，并将其作为实际故障影响程度；最后，通过对预测结果与实际故障影响程度进行仿真比较，验证了所建立的故障影响机理的合理性。     

基于改进粒子群算法辨识Volterra级数的目标机动轨迹预测

目标机动轨迹预测是空战态势感知和目标威胁评估的重要前提。针对传统目标机动轨迹预测模型复杂度大、预测精度低等问题，结合目标机动轨迹时间序列的混沌特性，提出一种基于相空间重构理论和Volterra泛函级数的目标机动轨迹预测模型。该模型首先采用0-1检测法验证了目标机动轨迹时间序列具有混沌特性；其次，利用C-C法确定嵌入维数和时间延迟，对目标机动轨迹时间序列进行了相空间重构；然后，引入Volterra泛函级数预测模型，为了克服高阶Volterra核函数求解复杂的难题，提出一种混沌变异自适应粒子群算法，构建一种基于改进粒子群算法辨识的Volterra级数预测模型，并将其应用于目标机动轨迹预测；最后，将所提算法与卡尔曼滤波算法以及机器学习算法进行单步和多步预测对比，同时将改进粒子群算法与其他智能算法进行性能比较。仿真结果表明：所提预测模型具有良好的单步和多步预测性能，改进的粒子群算法具有参数辨识精度高、收敛速度快的优点。     

管制-飞行状态相依网络演化过程

动态、准确的管制系统运行态势预测是航空运输系统各相关单位开展协同决策的关键基础。基于航空器间的冲突情况、管制员对航空器的管控情况以及管制移交情况构建管制-飞行状态相依网络,探究、分析其演化规律,采用相关性分析和主成分分析证明了所选5项指标的合理性。设置自由飞行和固定航线飞行两种仿真场景,通过计算平均节点度、平均点强等拓扑指标的最大李雅普诺夫指数证明各时间序列均具有混沌特性,选择长短期记忆（LSTM）人工神经网络方法对各时间序列的演化规律进行预测,并与其他预测算法进行对比。仿真结果表明LSTM算法能对管制系统的演化过程进行有效的预测,且预测精度高于贝叶斯算法和支持向量机算法;在自由飞行条件下,5项指标的预测误差绝大部分在20%以内,固定航线飞行的预测效果优于自由飞行。     

UKF-WNN及其在准定常失速气动力建模中的应用

提出一种利用无轨迹卡尔曼滤波估计小波网络参数的算法,该算法可克服算法存在的收敛速度慢、计算量大、局部极小等缺点。以飞机的准定常失速现象的气动力建模为应用背景,分别运用BP算法,扩展卡尔曼滤波算法和无轨迹卡尔曼滤波算法训练小波网络。仿真结果表明,无轨迹卡尔曼滤波算法较之BP算法和扩展卡尔曼滤波算法具有更快的训练速度和更高的预测精度,可以胜任复杂的非线性气动现象的建模任务。     

基于扩展卡尔曼滤波的小型固定翼无人机姿态估计方法分析

随着小型固定翼无人机的发展,由于其成本低、体积小的特点受到越来越多的企业青睐,但是由于成本问题,导致大部分企业只能选择成本较低的传感器,因此,针对固定翼无人机的姿态估计变得困难。为了解决这个问题,需要研究出一种新的姿态估计方法。利用离散型扩展卡尔曼滤波原理,结合常用的惯性导航系统和卫星定位系统,对小型无人机姿态进行估计解算。仿真结果显示,该方法可以准确地估计出无人机的姿态信息,其最大误差不超过2°,通过与未进行滤波算法处理的结果相比较,大大地减小了姿态估计的误差,因此这种基于扩展卡尔曼滤波的姿态估计算法针对小型无人机的姿态估计是可靠的。     

基于DKF的IMU误差预测算法

作为导航领域常用的组合导航方式,全球导航卫星系统(GNSS)/惯性导航系统(INS)组合导航在GNSS信号失锁后,由于惯性测量单元(IMU)误差随时间迅速积累,其定位结果会偏离载体真实位置,导航精度下降.针对此问题,提出了一种长短期记忆网络(LSTM)辅助的算法,称之为深度卡尔曼滤波(DKF)算法.DKF算法的核心思想是使用LSTM训练IMU误差模型,然后通过训练出的模型预测IMU误差,最后将预测的IMU误差代入IMU数据以校正导航结果.仿真结果表明:在200s测试数据上,DKF算法将误差从1.1537m/s降低到0.3746m/s.与平均预测、卡尔曼预测和最小二乘估计等方法相比,DKF算法的误差最小,具有更优越的导航性能.     

基于Elman神经网络的战斗机空战轨迹预测

轨迹预测是空战态势感知中的关键问题。针对传统轨迹预测方法模型简化程度大、预测精度偏低的问题,提出了基于Elman神经网络的战斗机空战轨迹预测方法。首先,以一对一空战为背景,建立了基于Elman神经网络的目标机空战轨迹预测模型;其次,在利用空战训练测量仪(ACMI)中记录的空战数据基础上,选取了一对一空战轨迹,并构建了训练样本和测试样本;然后,通过仿真分析了不同算法进行轨迹预测的精度。结果表明,与传统粒子滤波算法相比,Elman网络模型预测误差更小、预测效果更好,可以更加准确地进行目标机空战轨迹的预测。     

基于轨迹映射的无人机拖曳式空中回收轨迹优化

针对无人机拖曳式空中回收过程中的轨迹优化问题，提出一种基于轨迹映射的无人机回收轨迹在线优化方法。首先，建立包括缆绳-浮标-无人机组合体的运动模型、机翼折叠模型在内的空中回收系统模型。随后，提出轨迹映射的思想，利用双向长短期记忆（BiLSTM）神经网络建立回收系统中回收指令和回收轨迹之间的精确映射关系。然后，利用轨迹映射网络实时预测不同指令下的回收轨迹，并根据计算的预测轨迹代价利用粒子群优化（PSO）算法优化得到最佳回收指令。最后，仿真结果表明：所提的轨迹映射网络具有较高的预测精度和计算速度，所提的方法可以优化出使无人机稳定快速回收的轨迹。     

集群无人机队形重构及虚拟仿真验证

队形重构是集群无人机（UAV）控制的重要问题，指无人机按照要求安全、无碰撞地从一个队形变换到另一个队形，其难点在于快速规划最优安全轨迹并控制无人机进行轨迹姿态的高精度跟踪。针对集群无人机队形重构的上述问题，首先，基于CAPT（Concurrent Assignment and Planning of Trajectories）算法，解决了多无人机的目标分配和轨迹生成的实时性问题，实现了集群无人机的最优安全路径规划；其次，提出一种有限时间多变量积分滑模连续控制算法，解决了无人机轨迹姿态的高精度跟踪问题，并通过MATLAB仿真验证了该控制算法的有效性；最后，为了更加真实直观地演示无人机三维仿真效果，建立了基于Gazebo-ROS的无人机仿真平台，实现了12架四旋翼无人机队形重构"建模-仿真-可视化"的一体化仿真演示，验证了上述路径规划算法和轨迹姿态控制算法的有效性。     

面向无人机蜂群的航电云多层任务调度模型

在航空作战体系中，基于航电云的无人机（UAV）蜂群作战是提高未来无人机综合作战能力的一种新模式。针对无人机蜂群作战的航电云架构，如何将云端作战任务派发到无人机且保证作战任务完成时间是其中关键。在无人机蜂群分层分簇网络结构和模块级资源虚拟化的基础上，对传统单层平台级任务调度模型进行改进，提出了一种细化到模块级的多层任务调度模型，将作战任务从云端逐层调度到无人机功能模块上执行。利用OMNeT++对无人机蜂群多层任务调度模型以及传统的单层任务调度模型分别进行仿真，云端以攻击使命组为例构建使命组集进行分配，并对任务吞吐量、消息平均端到端延时和任务完成时间进行性能对比。仿真结果表明：与平台级单层任务调度相比，在执行任务方面，模块级多层任务调度模型将单个任务平均完成时间降低了46.2%，将使命组完成时间降低了52.1%，在保证任务吞吐量的基础上具有对复杂任务更稳定的调度能力；在网络性能方面，模块级多层任务调度模型消息端到端延时更低，延时分布更集中，提高了网络消息传输的实时性。     

The effect of inlet conditions on the flow and heat transfer in multiple rotating cavity with axial throughflow

This paper discusses experimental results from two different build configurations of a heated multiple rotating cavity test rig.Measurements of heat transfer from the discs and tangential velocities are presented.The test rig is a 70% full scale version of a high pressure compressor stack of an axial gas turbine engine.Of particular interest are the internal cylindrical cavities formed by adjacent discs and the interaction of these with a central axial throughflow of cooling air.Tests were carried out for a range of non-dimensional parameters representative of high pressure compressor internal air system flows(Re up to 5×106 and Rez up to 2×105).Two different builds have been tested.The most significant difference between these two build configurations is the size of the annular gap between the(non-rotating) drive shaft and the bores of the discs.The heat transfer data were obtained from thermocouple measurements of surface temperature and a conduction solution method.The velocity measurements were made using a two component,LDA system.The heat transfer results from the discs show differences between the two builds.This is attributed to the wider annular gap allowing more of the throughflow to penetrate into the cavity.There are also significant differences between the radial distributions of tangential velocity in the two builds of the test rig.For the narrow annular gap,there is an increase of non-dimensional tangential velocity V/Ωr with radial location to solid body rotation V/Ωr=1.For the wider annular gap,the non-dimensional velocities show a decrease with radial location to solid body rotation.      

Research on Auto-detection for Remainder Particles of Aerospace Relay Based on Wavelet Analysis

Aerospace relay is one kind of electronic components which is used widely in national defense system and aerospace system. The existence of remainder particles induces the reliability declining, which has become a severe problem in the development of aerospace relay. Traditional particle impact noise detection (PIND) method for remainder detection is ineffective for small particles, due to its low precision and involvement of subjective factors. An auto-detection method for PIND output signals is proposed in this paper, which is based on direct wavelet de-noising (DWD), cross-correlation analysis (CCA) and homo-filtering (HF), the method enhances the affectiv-ity of PIND test about the small particles. In the end, some practical PIND output signals are analysed, and the validity of this new method is proved.     

Preparation of Highly Dispersed Antimony-doped Tin Oxide Nano-powder via Ion-exchange Hydrolysis of SnCl4 and SbCl3 and Azeotropic Drying

Antimony-doped tin hydroxide colloid precipitates have been synthesized by hydrolysis of SnCl4 and SbCl3 using: (1) an ion-exchange hydrolysis to remove chlorine ions, and (2) isoamyl acetate as an azeotropic solvent to obviate water. The obtained dried powder is of high dispersivity without any need for further grinding. The size and dispersivity of the final particles are investigated with the aid of TG-DTA, BET, XRD and TEM. After having calcined, the antimony-doped tin oxide nanopowder possesses a tetragonal rutile structure with high dispersivity, uniform particles and low hard agglomeration.     

Effects of Mo on the Microstructure and Hydrogen Sorption Properties of Ti-Mo Getters

The effects of Mo on the microstructure evolution, porosity and hydrogen sorption properties of Ti-Mo getters are investigated in this work. The results show that the addition of Mo prolongs the densification process of Ti-Mo getters and results in a significant amount of sintered pores. With the Mo content increasing, the porosity of getters firstly increases reaching the maximum value as it at- tains about 7.5wt.%, and then drops. At the room temperature, the hydrogen sorption property of getters increases progressively with the Mo content increasing, but the tendency is not very clear before its content lies below 2.5wt.%. When the Mo content achieves about 7.5wt.%, the hydrogen sorption property proves to be the best. The discussion is made about the above mentioned phenomena inclusive of hydrogen sorption properties of getters under different activation conditions (from 500-750 ℃).     

超声速燃烧数值模拟中的湍流与化学反应相互作用模型

高精度数值模拟有助于理解超声速湍流燃烧中湍流与化学反应的相互作用,可为发动机燃烧室等工程应用设计提供可靠的预测模型。除直接数值模拟外,目前在湍流燃烧应用中使用的大涡模拟和雷诺平均Navier-Stokes模拟均需要借助模型模化发生在湍流小尺度上的流动与化学反应过程对湍流大尺度运动的影响。现有的湍流与化学反应相互作用模型大致可分为:火焰面类模型和概率密度函数类模型,2类模型在不同的应用中各自具有优势和局限性。此外,现有模型大都基于低马赫数燃烧,而超声速燃烧中通常会伴随快速混合、局部熄火和再着火以及激波等复杂过程,这为发展其中的湍流与化学反应相互作用模型提出了更多的挑战。     

适于低轨卫星IP网络的单核共享树组播算法(英文)

为了解决低轨卫星IP网络中现有典型源组播算法的信道资源浪费问题,本文提出了一套单核共享树组播算法,即核心群合并共享树(CCST)和加权核心群合并共享树(w-CCST)算法。CCST 算法包括动态近似中心(DAC)选核方法和核心群合并组播路径构建方法。DAC方法专为周期、规律运动的低轨卫星网络提出,不需要复杂的星上计算。在核心群合并方法中,以核节点作为初始核心群,通过核心群和剩余组成员的最短路径方法逐步扩展直至整棵组播树构建完成,从而使得组播树的树代价最小,大大提高了网络的带宽利用率和组播传输效率。w-CCST 算法中所提出的加权因子可以调整树代价和端到端传播时延之间的折衷程度,因此,可以通过调整加权因子来适度增大树代价、降低端到端传播时延以支持某些端到端时延要求苛刻的实时组播业务。最后,与低轨卫星 IP 网络中典型算法进行了性能比较,仿真结果说明,CCST 算法的平均树代价比其它算法显著降低,w-CCST 算法的平均端到端传播时延小于 CCST 算法。     

Jet Vectoring Control Using a Novel Synthetic Jet Actuator

A primary air jet vectoring control system with a novel synthetic jet actuator (SJA) is presented and simulated numerically. The results show that, in comparison with an existing traditional synthetic jet actuator, which is able to perform the duty of either “push” or “pull”, one novel synthetic jet actuator can fulfill both “push” and “pull” functions to vector the primary jet by shifting a slide block inside it. Therefore, because the new actuator possesses greater efficiency, it has potentiality to replace the existing one in various appli- cations, such as thrust vectoring and the reduction of thermal signature. Moreover, as the novel actuator can fulfill those functions that the existing one can not, it may well be expected to popularize it into more flow control systems.     

Nonlinear Adaptive Slewing Motion Control of Spacecraft Truss Driven by Synchronous V-gimbaled CMG Precession

The slewing motion control of a truss arm driven by a V-gimbaled control-moment-gyro (CMG) is a nonlinear control problem. The V-gimbaled CMG consists of a pair of gyros that must precess synchronously. The moment of inertia of the system, the angular momentum of the gyros and the external disturbances are not exactly known. With the help of feedback linearization and recursive Lyapunov design method, an adaptive nonlinear controller is designed to deal with the unknown items. Performance of the proposed controller is verified by simulation.     

An SOR Implicit Time-accurate Scheme in Calculating Unsteady Flows

A new time-accurate marching scheme for unsteady flow calculations is proposed in the present work. This method is the combination of classical Successive Over-Relaxation (SOR) iteration method and Jacobian matrix diagonally dominant splitting method of LUSGS. One advantage of this algorithm is the second-order accuracy because of no factorization error. Another advantage is the low computational cost because the Jacobian matrices and fluxes are only calculated once in each physical time step. And, the SOR algorithm has better convergence property than Gauss-Seidel. To investigate its accuracy and convergency, several unsteady flow computa- tional tests are carried out by using the proposed SOR algorithm. Roe’s FDS scheme is used to discritize the inviscid flux terms. Un- steady computational results of SOR are compared with the experiment results and those of Gauss-Seidel. Results reveal that the numerical results agree well with the experimental data and the second-order accuracy can be obtained as the Gauss-Seidel for unsteady flow computations. The impact of SOR factor is investigated for unsteady computations by using different SOR factors in this algorithm to simulate each computational test. Different numbers of inner iterations are needed to converge to the same criterion for different SOR factors and optimal choice of SOR factor can improve the computational efficiency greatly.