Assessment of Meteorological Threats to the Coordinated Search and Rescue of Unmanned/Manned Aircraft

The architecture and working principle of coordinated search and rescue system of unmanned/manned aircraft,which is composed of manned/unmanned aircraft and manned aircraft,were first introduced,and they can cooperate with each other to complete a search and rescue task.Secondly,a threat assessment method based on meteorological data was proposed,and potential meteorological threats,such as storms and rainfall,can be predicted by collecting and analyzing meteorological data.Finally,an experiment was carried out to evaluate the performance of the proposed method in different scenarios.The experimental results show that the coordinated search and rescue system of unmanned/manned aircraft can be used to effectively assess meteorological threats and provide accurate search and rescue guidance.

Simulation Analysis of Electromechanical Coupling for Unmanned Aerial Vehicle Cabin Door System

In order to study the dynamic response of the unmanned aerial vehicle cabin door opening and closing system under impact load conditions, considering the flexible treatment of mechanical components, and the system’s motion with different stiffness of energy-absorbing components, a rigid-flexible coupling model of the cabin door actuation system was established in LMS. Virtual. Motion. In Amesim, a control model of the motor was created. Through the Motion-Amesim co-simulation module, the dynamic module of the system was combined with the motor control module to complete the electromechanical coupling simulation and analyze the results. .

Isopropanol as Fuel for Small Unmanned Aircraft

Gasoline engines are increasingly popular for use in small unmanned aircraft requiring endurance due to the specific energy of gasoline (47.3 MJ·kg-1) and its cost effectiveness. However, gasoline is volatile and it poses a health hazard. In this work, isopropanol is proposed and investigated as viable fuel for small gasoline engines. Isooctane is used as a benchmark for performance comparison. The field testing reveals that isopropanol offers similar running performance and ease of starting. The maximum output power of isopropanol is surprisingly found to occur at a more advanced ignition timing compared with isooctane. The significant outcome of this study is that isopropanol can readily be used as a replacement fuel for existing engines without the need for any modifications to the ignition module or the engine itself.

Theoretical Investigations on Mapping Mean Distributions of Particulate Matter,Inert,Reactive,and Secondary Pollutants from Wildfires by Unmanned Air Vehicles(UAVs)

Evaluated Weather Research and Forecasting model inline with chemistry (WRF/Chem) simulations of the 2009 Crazy Mountain Complex wildfire in Interior Alaska served as a testbed for typical Alaska wildfire-smoke conditions. A virtual unmanned air vehicle (UAV) sampled temperatures, dewpoint temperatures, primary inert and reactive gases and particular matter of different sizes as well as secondary pollutants from the WRF/Chem results using different sampling patterns, altitudes and speeds to investigate the impact of the sampling design on obtained mean distributions. In this experimental design, the WRF/Chem data served as the “grand truth” to assess the mean distributions from sampling. During frontal passage, the obtained mean distributions were sensitive to the flight patterns, speeds and heights. For inert constituents mean distributions from sampling agreed with the “grand truth” within a factor of two at 1000 m. Mean distributions of gases involved in photochemistry differed among flight patterns except for ozone. The diurnal cycle of these gases’ concentrations led to overestimation (underestimation) of 20 h means in areas of high (low) concentrations as compared to the “grand truth.” The mean ozone distribution was sensitive to the speed of the virtual UAV. Particulate matter showed the strongest sensitivity to the flight patterns, especially during precipitation.

Unmanned Aerial Vehicles:Control Methods and Future Challenges

With the rapid development of computer technology,automatic control technology and communication technology,research on unmanned aerial vehicles(UAVs)has attracted extensive attention from all over the world during the last decades.Particularly due to the demand of various civil applications,the conceptual design of UAV and autonomous flight control technology have been promoted and developed mutually.This paper is devoted to providing a brief review of the UAV control issues,including motion equations,various classical and advanced control approaches.The basic ideas,applicable conditions,advantages and disadvantages of these control approaches are illustrated and discussed.Some challenging topics and future research directions are raised.

Distributed tracking control of unmanned aerial vehicles under wind disturbance and model uncertainty

A distributed robust method is developed for cooperative tracking control of unmanned aerial vehicles under unknown wind disturbance and model uncertainty. The communication network among vehicles is a directed graph with switching topology. Each vehicle can only share its states with its neighbors. Dynamics of the vehicles are nonlinear and affected by the wind disturbance and model uncertainty. Feedback linearization is adopted to transform the dynamics of vehicles into linear systems. To account for the wind disturbance and model uncertainty, a robust controller is designed for each vehicle such that all vehicles ultimately synchronize to the virtual leader in the three-dimensional path. It is theoretically shown that the position states of the vehicles will converge to that of the virtual leader if the communication network has a directed spanning tree rooted at the virtual leader. Furthermore, the robust controller is extended to address the formation control problem. Simulation examples are also given to illustrate the effectiveness of the proposed method. © 2016 Beijing Institute of Aerospace Information.

Failure analysis of unmanned autonomous swarm considering cascading effects

In this paper, we focus on the failure analysis of unmanned autonomous swarm(UAS) considering cascading effects. A framework of failure analysis for UAS is proposed.Guided by the framework, the failure analysis of UAS with crash fault agents is performed. Resilience is used to analyze the processes of cascading failure and self-repair of UAS. Through simulation studies, we reveal the pivotal relationship between resilience, the swarm size, and the percentage of failed agents.The simulation results show that the swarm size does not affect the cascading failure process but has much influence on the process of self-repair and the final performance of the swarm.The results also reveal a tipping point exists in the swarm. Meanwhile, we get a counter-intuitive result that larger-scale UAS loses more resilience in the case of a small percentage of failed individuals, suggesting that the increasing swarm size does not necessarily lead to high resilience. It is also found that the temporal degree failure strategy performs much more harmfully to the resilience of swarm systems than the random failure. Our work can provide new insights into the mechanisms of swarm collapse, help build more robust UAS, and develop more efficient failure or protection strategies.

Intent Inference Based Trajectory Prediction and Smooth for UAS in Low-Altitude Airspace with Geofence

In order to meet the higher accuracy requirement of trajectory prediction for Unmanned Aircraft System(UAS)in Unmanned Aircraft System Traffic Management(UTM),an Intent Based Trajectory Prediction and Smooth Based on Constrained State-dependent-transition Hybrid Estimation(CSDTHE-IBTPS)algorithm is proposed.Firstly,an intent inference method of UAS is constructed based on the information of ADS-B and geofence system.Moreover,a geofence layering algorithm is proposed.Secondly,the Flight Mode Change Points(FMCP)are used to define the relevant mode transition parameters and design the guard conditions,so as to generate the mode transition probability matrix and establish the continuous state-dependent-transition model.After that,the constrained Kalman filter(CKF)is applied to improve State-dependent-transition Hybrid Estimation(SDTHE)algorithm by applying equality constraint to the velocity of UAS in the straight phase and turning phase,respectively,and thus the constrained state-dependent-transition hybrid estimation(CSDTHE)algorithm is constructed.Finally,the results of intent inference and hybrid estimation are used to make trajectory prediction.Furthermore,each flight segment of trajectory is smoothed respectively by Rauch-Tung-Striebel(RTS)backward smooth method using the proposed CSDTHE-RTS algorithm,so as to obtain more accurate trajectory prediction results.The simulation shows that the proposed algorithm can reduce the errors of trajectory prediction and the time delay of intent inference.

Trajectory Tracking of Vertical Take-off and Landing Unmanned Aerial Vehicles Based on Disturbance Rejection Control

We investigate the trajectory tracking problem of vertical take-off and landing(VTOL) unmanned aerial vehicles(UAV), and propose a practical disturbance rejection control strategy. Firstly, the nonlinear error model is established completely by the modified Rodrigues parameters, while considering dynamics of the servo actuators. Then, a hierarchical control scheme is applied to design the translational and rotational controllers based on the time-scale property of each subsystem,respectively. And the linear extended state observer and auxiliary observer are used to deal with the uncertainties and saturation.At last, global stability of the closed-loop system is analyzed based on the singular perturbation theory. Simulation results show the effectiveness of the proposed control strategy.

Autonomous UAV 3D trajectory optimization and transmission scheduling for sensor data collection on uneven terrains

This paper considers a time-constrained data collection problem from a network of ground sensors located on uneven terrain by an Unmanned Aerial Vehicle(UAV),a typical Unmanned Aerial System(UAS).The ground sensors harvest renewable energy and are equipped with batteries and data buffers.The ground sensor model takes into account sensor data buffer and battery limitations.An asymptotically globally optimal method of joint UAV 3D trajectory optimization and data transmission schedule is developed.The developed method maximizes the amount of data transmitted to the UAV without losses and too long delays and minimizes the propulsion energy of the UAV.The developed algorithm of optimal trajectory optimization and transmission scheduling is based on dynamic programming.Computer simulations demonstrate the effectiveness of the proposed algorithm.

不同海况条件下舰载无人机着舰安全分析

针对无人机上舰的使用需求,本文对舰载无人机着舰开展了系统的研究。建立了机-舰-环境综合模型和舰载无人机全自动着舰引导控制系统;基于建立的舰载无人机着舰综合模型对不同海况下的着舰过程进行仿真分析,研究不同海况条件以及航母不同航速和遭遇角对着舰安全的影响。仿真研究表明:在复杂海况下,航母可通过适当提高航速以获得更高的着舰成功率,但过高的航速会导致舰尾流扰动加剧,使得着舰成功率显著下降;通过对仿真结果进行统计分析,给出了不同海况下的着舰安全范围,为无人机着舰辅助决策提供参考。

航母舰载无人机全自动着舰技术特点分析

全自动着舰技术是无人机上舰必须解决的“使能”技术。2013年,美军已完成X-47B无人机验证机在航母上的全自动着舰试验验证,为其发展MQ-25A“黄貂鱼”航母舰载无人机装备奠定了良好的技术基础。在梳理飞机着陆与着舰差异的基础上,给出航母舰载无人机全自动着舰的通用流程;从地位作用、工作范围、系统构架、系统要求、实现手段以及关键技术支撑等角度,对比有人机重点分析了航母舰载无人机全自动着舰的特点,为后续关键技术研究和武器装备建设发展提供参考。

UAV集群自组织飞行建模与控制策略研究

针对多无人航空器协同控制难题,聚焦无人航空器集群(unmanned aircraft vehicles swarm,UAVS)自组织飞行建模与控制展开研究。基于集群智能理论建立了UAVS系统概念模型,在考虑个体排斥作用、一致作用、吸引作用和个体行动意愿作用4种因素的情况下建立了集群运动的变系数(repulsion-matching-attracting-desire,RMAD)控制器模型,以此为基础,研究了所有个体掌握航迹信息和部分个体掌握航迹信息两种情况下UAVS自组织飞行控制问题,提出UAVS自组织飞行控制策略,实现了UAVS可控性自组织飞行。仿真实验结果表明构造的UAVS运动的RMAD模型及控制方法是可行的,为UAVS的工程应用奠定理论和实验基础。

一种改进的UAV三维航迹实时规划算法

航迹规划对于战场环境中无人机完成其作战任务具有非常重要的意义.针对真实战场环境中低空无人机的三维航迹实时规划问题,构建了一个更加真实的战场威胁精简模型;提出遗传个体的基因优劣对比度,改进一种共享小生境遗传算法中编码基因的遗传特性.经过改进,增大优化基因的遗传概率,实现提高小生境遗传算法的全局优化能力和收敛速度,增强航迹规划的实时性.对三维数字地形空间进行定长网格编码,将改进的小生境遗传算法应用于三维虚拟战场环境中的无人机航迹规划,实验验证了改进算法的有效性,并能满足在线航迹规划的实时性要求.

临近空间UAV路径衰落的自适应Markov模型

在分析临近空间UAV(无人机)飞行特征的基础上,根据临近空间UAV的飞行状态——发射和降落状态、航空飞行状态、飞行盘旋状态,结合临近空间的物理环境,建立了临近空间长航时UAV路径衰落的自适应Markov模型,提出了具体的理论分析过程和实现方法;给出了各个状态下动态信道的路径衰落理论计算式,最后实现了临近空间UAV自适应Markov路径衰落模型的自由空间衰落、双径衰落和多径衰落仿真,从而保证了模型的可靠性。仿真得出:在临近空间UAV的通信中,其路径衰落主要考虑自由空间衰落量和反射分量,但多径分量不容忽视。

基于多传感器融合的无人舰载机舰面定位研究

无人舰载机在航母舰面的自主定位是实现自主转运、提高驶入/驶出效率的重要前提.其中,如何依靠机载传感设备实现GPS拒止环境下的舰载机自主舰面定位是亟待解决的关键技术.为此,提出了一种基于视觉和激光雷达融合的无人舰载机舰面自主定位算法.该算法通过结合手眼标定和互信息标定方法进行多传感器在线标定,使无人舰载机在面对风浪及航母运行等情况下机身摇晃导致传感器外参标定结果变化后仍能保持稳定运行;引入因子图用于无人舰载机的多传感器位姿联合优化并基于自主转运过程中的运动模型建立了简单高效的传感器失效标准,从而有效地融合了激光雷达和视觉定位结果,使该算法在单个传感器失效的情况下依然可以进行精确的自主定位;最后建立了基于多传感器的舰载机舰面仿真系统对本文算法进行验证,实验结果表明,本文算法在单个传感器失效的情况下定位误差仍维持在0.2m以内,满足实际应用要求.

无人机集群弹性评估及重构技术研究

无人机集群在实际应用中常受地形地貌、风雪雨雾、防空打击等扰动因素影响,导致集群性能下降、任务完成能力降低。为有效评估和提升集群抗扰能力,从无人机集群弹性评估指标和弹性重构方法两方面展开深入研究。梳理分析无人机集群弹性评估指标研究现状;从预测性重构和抗扰动重构两方面对无人机集群弹性重构方法进行了研究总结;针对评估指标不全面及多任务、多扰动情况下集群无法自适应重构问题,分别提出多维弹性评估指标和无人机集群相变重构方法,进一步考虑了覆盖率、能耗等因素对集群性能的影响,实现了不同任务类型和扰动种类自适应相变,大幅提升了集群应对扰动能力。最后,总结展望无人机集群弹性重构未来发展趋势。

基于改进蚁群算法的凹区域无人侦察机覆盖航线规划

针对固定翼无人机的区域覆盖侦察航线规划问题,提出一种基于改进蚁群算法的凹区域覆盖航线规划方法。建立垂直载荷侦察模型,引入平行覆盖策略,通过旋转卡壳法确定飞行方向;针对不规则凹多边形区域,提出融合凹点移除和区域分解的多策略凹多边形转换方法;将覆盖航线规划问题转换为搜索最优条带遍历顺序的优化问题,建立Dubins转弯航线,通过在蚁群算法中改进启发函数、引入自适应信息素挥发系数和3-opt算法进行问题求解。实验结果表明,该方法能够高效实现凹区域转换,并获得长度更短的区域覆盖侦察航线,可为开展无人侦察机自主区域侦察研究提供理论支持。

大载荷油动植保无人机喷雾参数对棕榈树冠层雾滴沉积分布的影响

对使用大载荷油动植保无人机对棕榈树进行喷施作业的效果进行了评价,探讨了植保无人机喷洒参数对棕榈树上雾滴沉积的影响。以大载荷油动植保无人机为研究对象,进行了正交试验,考察了3个因素:飞行高度、飞行速度和喷头流量。经过试验比较,当喷头流量为3.4 L/min、作业高度为3 m、作业速度为3 m/s时,雾滴沉积密度和均匀性最佳。其中,喷头流量对雾滴沉积密度的影响最大,其次是作业高度和作业速度;在穿透性方面,喷头流量为3.4 L/min、作业高度为4 m、作业速度为4 m/s和喷头流量为4.2 L/min、作业高度为4 m、作业速度为3 m/s,其雾滴的穿透性较强,分别为15.83%和30.01%。影响雾滴沉积穿透性的因素依次为喷头流量、作业高度和作业速度。本试验对大载荷油动植保无人机在棕榈树合理喷施和提高喷施效果方面具有参考价值。