基于佘度和容错技术的高可靠机载智能配电系统设计

针对大型无人机(UAV)用常规配电系统占用航空总线资源多和可靠性低的问题,通过研究多电/全电飞机技术发展趋势和大型无人机供电系统技术特点,提出一种适用于大型无人机体系结构和指标要求的机载智能配电系统;建立系统的马尔可夫模型,计算和分析不同余度结构的供电处理机(PSP)和电气负载管理中心(ELMC)对系统可靠性的影响,进...     

Optimization of efficient order service by information unmanned aerial vehicles

We propose a mathematical model and the numerical method for an optimal choice of unmanned aerial vehicles (UAVs) from those being in flight to fulfill a newly received order for monitoring (reconnaissance) of a new region. Examples of using the approach being proposed and main lines of its realization in promising information unmanned aircraft complexes (UAC) are presented.     

Flight safety measurements of UAVs in congested airspace

Describing spatial safety status is crucial for high-density air traffic involving multiple unmanned aerial vehicles (UAVs) in a complex environment. A probabilistic approach is proposed to measure safety situation in congested airspace. The occupancy distribution of the airspace is represented with conflict probability between spatial positions and UAV. The concept of a safety envelope related to flight performance and response time is presented first instead of the conventional fixed-size protected zones around aircraft. Consequently, the conflict probability is performance-dependent, and effects of various UAVs on safety can be distinguished. The uncer-tainty of a UAV future position is explicitly accounted for as Brownian motion. An analytic approximate algorithm for the conflict probability is developed to decrease the computational consumption. The relationship between safety and flight performance are discussed for different response times and prediction intervals. To illustrate the applications of the approach, an experi-ment of three UAVs in formation flight is performed. In addition, an example of trajectory planning is simulated for one UAV flying over airspace where five UAVs exist. The validation of the approach shows its potential in guaranteeing flight safety in highly dynamic environment.     

基于软件的无人机故障注入技术研究

故障注入是一种用于容错计算机系统验证的有效技术,其应用效果直接取决于所采用的故障注入方法的正确性。文中采用硬件覆盖和故障模型的方法,模拟无人机系统的硬件故障,并着重讨论了在总线上注入故障的试验策略。然后用软件的方法构造了一个用于测评无人机飞行控制系统容错控制机制的故障注入工具UAVFI_01。在无人机动态测试过程中,故障注入试验结果表明了这种方案的正确性和可行性。     

无人机滑橇缓冲装置动力学仿真分析

着陆缓冲装置的性能主要依靠缓冲器来实现,而缓冲器的仿真建模是虚拟样机设计的关键,传统的缓冲器建模方法主要采用理论公式法,其精度较难确定。根据无人机的使用要求,设计一种适用于伞降回收的滑橇缓冲方案;运用缓冲器静压试验及缓冲器落震试验数据曲线建立缓冲器动力学模型;基于缓冲器动力学模型研究全机多刚体落震模型,对无人机着陆缓冲过程的动态特性进行仿真分析;应用有限元技术对滑橇结构动态响应进行非线性动力学仿真分析,并根据仿真结果优化滑橇缓冲装置设计参数。结果表明:仿真结果与全机落震试验结果相吻合;所建立的无人机落震模型精度较高,满足工程需要,能极大地减少试验成本,缩短研制周期。     

Simulation Environment for Machine Vision Based Aerial Refueling for UAVs

The design of a simulation environment is described for a machine vision (MV)-based approach for the problem of aerial refueling (AR) for unmanned aerial vehicles (UAVs) using the USAF refueling method. MV-based algorithms are implemented within the proposed scheme to detect the relative position and orientation between the UAV and the tanker. Within this effort, techniques and algorithms for the visualization the tanker aircraft in a virtual reality (VR) setting, for the acquisition of the tanker image, for the feature extraction (FE) from the acquired image, for the feature matching (FM) of the features, for the tanker-UAV pose estimation (PE) have been developed and extensively tested in closed-loop simulations. Detailed mathematical models of the tanker and UAV dynamics, refueling boom, turbulence, wind gusts, and tanker's wake effects, along with the UAV docking control laws have been implemented within the simulation environment. This paper also presents the results of a study relative to the use of passive markers versus feature extraction for the problem of estimating in real time the UAV-tanker relative position and orientation vectors.     

Detection and diagnosis of sensor and actuator failures using IMMestimator

An approach to detection and diagnosis of multiple failures in a dynamic system is proposed. It is based on the interacting multiple-model (IMM) estimation algorithm, which is one of the most cost-effective adaptive estimation techniques for systems involving structural as well as parametric changes. The proposed approach provides an integrated framework for fault detection, diagnosis, and state estimation. It is able to detect and isolate multiple faults substantially more quickly and more reliably than many existing approaches. Its superiority is illustrated in two aircraft examples for single and double faults of both sensors and actuators, in the forms of “total”, “partial”, and simultaneous failures. Both deterministic and random fault scenarios are designed and used for testing and comparing the performance fairly. Some new performance indices are presented. The robustness of the proposed approach to the design of model transition probabilities, fault modeling errors, and the uncertainties of noise statistics are also evaluated     

基于交互多模估计策略的故障检诊方法

针对多模自适应（ＭＭＡＥ）故障检诊（ＦＤＤ）方法的局限性,提出了一种基于交互多模（ＩＭＭ）估计策略的动态系统中多重故障的检诊方法。交互多模估计是针对包含有结构以及参数的系统的一种效率较好的自适应估计技术,它提供了故障检测、诊断和状态估计的集中框架。通过对在传感器和作动器中含有多个故障飞机的仿真。结果表明,所提供的方法比其它方法能够更快、更可靠地检测和隔离出多重故障。     

多无人机协同编队飞行控制的研究现状

多无人机（UAVs）编队飞行的协同侦察、作战模式可以在一定程度上提高单机单次作战任务的成功概率,因而引起各国对多机编队飞行的研究热潮。针对这一情形,在介绍了多UAV协同编队飞行（CFF）的定义和应用特点的基础上,结合近年来国内外多UAV编队飞行的发展状况和一些主要的研究成果,着重分析和讨论了编队飞行控制中几个相关的关键技术问题,主要包括：队形设计、气动耦合、队形的动态调整、航迹规划、信息互换以及编队飞行控制策略等问题;最后对未来的发展趋势进行了展望。研究成果对正在研究的多机作战平台系统的协同作战技术具有一定的参考意义。     

Pop-up threat models for persistent area denial

Pop-up threats usually appear or disappear randomly in a battle field. If the next pop-up threat locations could be predicted it would assist a search or attack team, such as in a persistent area denial (PAD) mission, in getting a team of unmanned air vehicles (UAVs) to the threats sooner. We present a Markov model for predicting pop-up ground threats in military operations. We first introduce a general Markov chain of order n to capture the dependence of the appearance of pop-up threats at previous locations of the pop-up threats over time. We then present an adaptive approach to estimate the stationary transition probabilities of the nth order Markov models. To choose the order of the Markov chain model for a specific application, we suggest using hypothesis tests from statistical inference on historical data of pop-up threat locations. Anticipating intelligent responses from an adversary, which might change its pop-up threat deployment strategy upon observing UAV movements, we present adaptive Markov chain models using a moving horizon approach to estimate possibly abrupt changes in transition probabilities. We combine predicted and actual pop-up target locations to develop efficient cooperative strategies for networked UAVs. A theoretical analysis and simulation results are presented to evaluate the Markov model used for predicting pop-up threats. These results demonstrate the effectiveness of cooperative strategies using the combined information of threats and predicted threats in improving overall mission performance.     

航空发动机数控系统多故障识别

提出了一种基于模糊逻辑的航空发动机数控系统多故障的识别方法.首先采用Takagi-Sugeno(T-S)模糊模型描述一种涡喷发动机数控系统的非线性模型,然后应用全解耦奇偶方程进行多故障的检测和隔离,并结合卡尔曼滤波器识别出传感器和执行器故障参数.仿真结果表明,针对传感器和执行器同时发生故障的情况,此方法能有效检测故障,并能准确识别出故障参数.      

Optimal Cooperative Sensing using a Team of UAVs

The authors investigates the joint optimal estimation of both the position and velocity of a ground moving target (GMT) using pulse Doppler radars on-board unmanned aerial vehicles (UAVs). The problem of cooperative estimation using a UAV team and the optimization of the team's configuration to achieve optimal GMT position and velocity estimates are addressed. Based on the Cramer-Rao bound, the minimum achievable error variance of the GMT position and velocity estimates is derived. The expression of the minimum achievable estimation error variance for unbiased estimation provided by the Cramer-Rao bound is minimized yielding the optimal configuration of the UAV team. Our solution is complete in that it addresses various GMT tracking scenarios and an arbitrary number of UAVs. Optimal sensor geometries for typical applications are illustrated     

考虑协同航路规划的多无人机任务分配

针对多无人机任务分配与协同航路规划问题，以分布式合同网拍卖算法为基础，构建无人机集群任务拍卖架构与拍卖收益函数，结合模拟退火算法协调任务执行次序，采用A^*算法完成两任务点间航程预估，在任务分配阶段同步完成多无人机间协同航路的初规划，确定最佳任务执行次序，实现任务分配与协同航路规划的紧耦合。仿真结果表明，在考虑禁飞区、障碍威胁情况下，该算法能够有效完成多架无人机不同类型任务的分配，且目标分配、执行次序合理，总执行代价小，各机间负载均衡；在任务分配阶段考虑协同航路规划具有明显的效果，能够有效提高任务分配的合理性。     

无人机集群研究进展综述

集群行为是一种常见于自然界中鱼群、鸟群、蜂群等低等群居生物的集体行为，生物群中的个体仅依靠局部感知作用和简单的通信规则自主决定其运动状态，并且从简单的局部规则涌现出协同的整体行为。受此启发，提出了无人机集群作战的概念。无人机集群作战是指依靠大量低成本、速度快、适应能力强、易于携带和投射的无人机形成规模优势，从而取得战争的主动权。由于无人机集群技术的重要战略地位，中美俄等军事大国均开始重视无人机集群技术的持续发展。介绍了无人机集群的研究动机，从模型、协议和平台3个角度总结了研究方法，重点分析了几种典型作战模式以及涉及的若干关键技术。综上所述，集群技术在军事方面具有重要的应用价值，必将引领全新的作战模式。     

基于CFD的软式空中加油锥套气动特性研究

无人机空中加油缺少人为的观测与控制,若要进行自主控制下的空中加油,获取精准的气动数据则十分关键。基于CFD研究了国外某型锥套的气动特性,通过改变锥套支撑臂数量、空速以及稳定伞面积3个因素,构建了不同的三维子模型。利用数值计算分析了其对锥套气动参数的影响,并探究了影响规律。仿真结果表明,支撑臂数量和稳定伞面积均会影响阻力系数,而空速对阻力系数几乎没有影响。该方法可以用来预测影响因素发生变化时锥套阻力系数的变化趋势,为分析锥套气动特性提供了理论依据。     

基于零空间方法的四旋翼无人机避障与协同编队控制

针对四旋翼无人机在编队飞行执行任务时可能遭遇障碍物问题,考虑多无人机避障及机间避撞的需求,提出 1种基于零空间方法的四旋翼无人机避障与协同编队控制算法。首先,建立四旋翼无人机动力学模型,并建立虚拟控制量简化控制模型;其次,基于零空间方法进行避障与协同编队控制算法研究,将无人机任务执行分解为目标趋向任务、避障避撞任务和协同编队任务,并根据优先级进行任务融合得到期望速度;再次,基于 PID方法设计控制律;最后,通过仿真验证所提控制算法的有效性。所提方法可保证四旋翼无人机在编队飞行中遭遇障碍物时的飞行安全。     

Addressing Uncertainty in UAV Navigation Decision-Making

We present an analytic framework for modeling and measuring uncertainty for the scenario of unmanned aerial vehicles (UAVs) cooperatively searching for a moving target. Uncertainty exists in a UAVs assessment of teammate locations, target locations, and sensor results. As is frequently done, our framework employs probabilistic maps to represent uncertain information regarding the UAVs environment. We present new methods to update the probabilistic maps when information arrives from onboard sensors or teammate UAVs. When new information is missing or delayed, we propose a novel and straightforward diffusion approach to update probabilistic maps. The UAVs make navigation decisions based on response to potential fields generated by the probabilistic maps. Since map data have uncertainty, this leads to decision-making in uncertainty. We conclude by describing how uncertainty in the environment translates into a unique measure, velocity vector dispersion (D_V), which describes the uncertainty in the UAVs navigation decision. Thresholds related to D_V may be useful to guide real-time decision policies. We present simulation results that show how the use of diffusion affects the time to locate targets. We also describe how D_V varies during UAV flight and comment on its utility.     

基于模型拼接技术的四旋翼无人机全飞行包线建模

四旋翼无人机在军事和民用领域都有广泛的应用前景。然而，四旋翼无人机具有机载传感器准确性低与可靠性差、不同飞行条件下动力学模型差异大等特点。本文以四旋翼无人机为研究对象，系统地开展了飞行路径重构、频率域系统辨识、全飞行包线建模的相关研究工作。针对机载低成本传感器存在显著常值偏差与量测噪声统计学特性未知的缺点，采用基于EKF的飞行路径重构技术对在飞行试验中无人机的机体空速进行重构；针对不同飞行速度下四旋翼无人机动力学模型差异大的特点，采用频域法辨识得到不同飞行条件下的本体动力学模型；针对四旋翼无人机大跨域的高精度控制需求，利用模型拼接技术，系统性地提出了全飞行包线建模方案，经过验证，所提出模型拼接技术是准确可靠的。     

固定翼无人机航磁探测系统的磁补偿模型分析

近年来,无人机的应用日益广泛,逐渐用于航空物探。在使用固定翼无人机搭载磁力仪进行航磁测量时,必然引入飞行平台干扰,包括与机动无关的干扰和与机动有关的干扰。去除和飞机机动有关的磁干扰,即为磁补偿工作。航磁补偿的经典TOLLES-LAWSON模型将磁干扰分为剩余磁场、感应磁场和涡流磁场。对于固定翼无人机,涡流磁场可以不考虑,将剩余磁场和感应磁场合称为稳态干扰场。主要对飞机干扰的来源和性质进行分析,并在地面设计实验验证铁磁性材料的性质,以加深对磁补偿模型的假设和推导过程的理解。最后,在地面实验平台上测量了飞机磁干扰场的平面分布图,指导航空磁力仪的安装。在将TOLLES-LAWSON模型应用于固定翼无人机航磁探测系统的磁补偿工作时,无人机与有人机相比,在结构和材料方面都有较大差异,因此对模型的物理意义和假设条件的深入理解至关重要,此即本文所述工作成果的出发点。     

基于自适应滑模观测器的航空发动机故障诊断

为解决现有航空发动机基于模型的在线故障诊断方法存在对模型精度要求高等的问题,利用滑模方法设计一种自适应滑模观测器对航空发动机进行在线故障重构、诊断与隔离。对传感器故障和执行机构故障分别设计了重构算法,针对两者重构故障的特点提出了判断逻辑,讨论了设计参数对于观测效果与抖振的影响。 Matlab/Simulink仿真结果显示,重构的故障与实际故障基本吻合,对故障的诊断、隔离、定位具有良好效果,并对环境不确定性具有优良的鲁棒性。