PermissibleWind Conditions for Optimal Dynamic Soaring with a Small Unmanned Aerial Vehicle

Dynamic soaring is a flight maneuver to exploit gradient wind field to extend endurance and traveling distance.Optimal trajectories for permissible wind conditions are generated for loitering dynamic soaring as well as for traveling patterns with a small unmanned aerial vehicle.The efficient direct collection approach based on the Runge-Kutta integrator is used to solve the optimization problem.The fast convergence of the optimization process leads to the potential for real-time applications.Based on the results of trajectory optimizations,the general permissible wind conditions which involve the allowable power law exponents and feasible reference wind strengths supporting dynamic soaring are proposed.Increasing the smallest allowable wingtip clearance to trade for robustness and safety of the vehicle system and improving the maximum traveling speed results in shrunken permissible domain of wind conditions for loitering and traveling dynamic soaring respectively.Sensitivity analyses of vehicle model parameters show that properly reducing the wingspan and increasing the maximum lift-to-drag ratio and the wing loading can enlarge the permissible domain.Permissible domains for different traveling directions show that the downwind dynamic soaring benefitting from the drift is more efficient than the upwind traveling pattern in terms of permissible domain size and net traveling speed.

Path planning for unmanned aerial vehicles in surveillance tasks under wind fields

The optimal path planning for fixed-wing unmanned aerial vehicles(UAVs) in multi-target surveillance tasks(MTST) in the presence of wind is concerned.To take into account the minimal turning radius of UAVs,the Dubins model is used to approximate the dynamics of UAVs.Based on the assumption,the path planning problem of UAVs in MTST can be formulated as a Dubins traveling salesman problem(DTSP).By considering its prohibitively high computational cost,the Dubins paths under terminal heading relaxation are introduced,which leads to significant reduction of the optimization scale and difficulty of the whole problem.Meanwhile,in view of the impact of wind on UAVs' paths,the notion of virtual target is proposed.The application of the idea successfully converts the Dubins path planning problem from an initial configuration to a target in wind into a problem of finding the minimal root of a transcendental equation.Then,the Dubins tour is derived by using differential evolution(DE) algorithm which employs random-key encoding technique to optimize the visiting sequence of waypoints.Finally,the effectiveness and efficiency of the proposed algorithm are demonstrated through computational experiments.Numerical results exhibit that the proposed algorithm can produce high quality solutions to the problem.

Robust Adaptive Control Design for Rotorcraft Unmanned Aerial Vehicles Based on Sliding Mode Approach

This paper presents a nonlinear robust control design method for a generic rotorcraft unmanned aerial vehicle(RUAV). The control objective is to let the RUAV track some pre-defined time-varying position and heading trajectories. The proposed controller employs feedback linearization process to realize the dynamic decoupling control and applies adaptive sliding mode control to compensate for the parametric uncertainties and external disturbances. The global asymptotical stability is proved via stability analysis. Compared with the cascaded controller, the proposed controller demonstrates a superior tracking performance and robustness through numerical simulation in the presence of parametric uncertainties and unknown disturbances.

四旋翼无人机滑模-CPCMAC联合控制半物理仿真系统

针对四旋翼无人机强耦合、欠驱动、非线性等特点,以及在实际飞行过程中极易受到干扰的问题,对四旋翼无人机动力学模型进行分析,提出了一种基于联合的四旋翼无人机姿态控制算法,并在此基础上设计了四旋翼无人机半物理仿真系统。首先,针对非线性系统设计滑模控制器,选择跟踪航迹和翻滚角设计位置控制率和姿态控制率。其次,滑模控制器在实际应用中易产生震荡,利用基于信用积分的小脑模型神经网络(CPCMAC)来学习滑模控制的方式。最后,搭建基于LabVIEW的控制站,同Matlab/Simulink进行数据收发控制。仿真结果表明,在跟踪目标相同时,提出的四旋翼无人机滑模-CPCMAC联合控制相比于传统的比例积分微分(PID)控制和积分反步法控制优势明显,能够抑制超调和余差,在快速性和鲁棒性方面都更加优越。同时,构建的四旋翼无人机半物理仿真平台能清晰反馈出无人机参数的变化,应用预留的参数接口和地面控制站,降低了无人机飞控算法的开发难度,提高了开发效率,具有明显的实用价值。

改进CBBA算法的风电场无人机群巡检任务分配

提出一种基于改进的共识捆绑算法(CBBA)的多无人机风电场巡检任务分配方法。首先,根据风电机组基础信息,采用K-均值算法确定无人机数量和安放位置,并构建风电机组巡检价值评估函数,更为合理地评估各风电机组的巡检收益;然后,针对无人机的归巢返程问题,提出一种基于CBBA算法的任务包双向构建策略;最后,为克服传统CBBA算法中存在的因个体“贪婪”导致的整体效益下降问题,设计一种基于类别的奖励制度,以提高任务分配的合理性。试验表明,所提方法可根据风速、风向的变化制定相应的巡检任务分配方案,可为无人机群自主巡检风电场的任务分配提供可参考的方案。

基于无人机倾斜摄影和激光扫描的离岸海岛高精度实景三维重建

本文面向离岸海岛实景三维需求与技术挑战,以珠海市庙湾岛为观测对象,采用无人机倾斜摄影与激光扫描的方式进行离岸海岛的实景三维数据获取。详细介绍了无人机任务规划、地面控制与实景三维数据处理工作,以及基于无参数布料模拟滤波的DEM生成,最终通过检查点验证了数据的绝对精度。结果表明,获取的正射、倾斜影像总中误差分别为14.72、6.60 cm;点云、DSM、DEM高程中误差分别为3.10、6.20、7.11 cm,满足离岸海岛实景三维展示与调查管理的需求。

海上风机无人机巡检螺旋桨振力异常监测研究

在对海上风机巡检过程中,由于无人机螺旋桨振力振动信号数据量较大,且海上环境的复杂性和不稳定性增加了异常信号的干扰,使得异常信号的检测和识别更加困难。为此,该文提出一种海上风机无人机巡检螺旋桨振力异常监测方法。利用集成经验模态(EEMD)分解,处理无人机螺旋桨振力信号,提取固有模态分量(IMF);利用稀疏傅里叶变换,处理具有周期性成分的IMF组分,提取振动强度异常特征;引入多传感器信息决策融合网络结构,并利用神经网络对其展开融合和综合决策,最终实现无人机螺旋桨振力异常监测。实验结果表明,所提方法可以获取高准确率和高效率的螺旋桨振力异常监测结果。

基于风机建模的风力电站无人机航迹点规划策略研究

针对风力电站无人机自动巡检之前需要操作人员将3个风机叶片的位置调整呈“Y”字型,操作麻烦且费时低效的问题,文章提出了一种基于风机建模的风力电站无人机航迹点规划策略。首先通过拍摄制动状态下风机的主视图和俯视图,经图像处理估算出风机的航向角和风机叶片的旋转角,再结合已知风机的尺寸参数和相关经度、纬度、海拔高度坐标,以轮毂中心为原点建立相关4个坐标系并定义转换矩阵,并考虑航迹点到风机叶片的安全避障距离,经过坐标系转换计算出无人机针对该风机巡检的12个航迹点的经度、纬度、海拔高度坐标、云台旋转角度等航迹信息。无人机实地飞行结果表明,该航迹点规划策略能获取准确的自主飞行规划路径,对风机制动后的3个叶片角度无要求,可以大幅提高无人机对风机巡检的效率。

微小无人机旋翼动力系统性能测试实验教学平台开发

为了满足高等院校交通运输类专业无人机系统教学需求,设计并开发了微小无人机旋翼动力系统性能测试实验教学平台,主要由主体台架系统、控制和数据采集系统、数据显示和分析系统组成。依托该实验教学平台,进行了悬停和前飞状态的旋翼性能测试实验。实验结果表明:配合风洞系统,利用该实验教学平台能够实时获取旋翼动力系统主要性能参数;气动拉力和扭矩直接测量误差均低于0.5%,电流电压直接测量误差为0.2%,桨力效和系统力效间接测量误差均低于5%。该实验教学平台可应用于小型无人机旋翼动力系统性能分析的实验教学。

无人机天钩回收航迹控制系统设计与实现

天钩回收无人机在回收时对于航迹偏差等的控制精度要求苛刻,这对控制系统提出了挑战。提出一种用于无人机天钩回收航迹控制的新方法,设计无人机天钩回收航迹控制策略与流程,给出控制系统组成,基于某型无人机风洞试验数据,构建天钩回收无人机的线性化和非线性模型,利用优化L1航迹控制方法设计了航迹控制律,并在实际飞行试验中得到了应用,验证了所设计控制系统的正确性与工程实现性,最终的飞行试验结果表明,无人机能够在控制系统作用下实现精确天钩回收,且具有良好的动态特性。

强风干扰下固定翼无人机“元飞行”气动建模研究

强风干扰下的复杂空气动力学给固定翼无人机的安全稳定飞行带来了严峻挑战。为提高强风干扰下固定翼无人机的环境适应能力,发展了一种创新的“元飞行”气动建模方法。不同于传统气流系下的气动建模,“元飞行”气动建模是一种元方法论建模技术,其采用易于测量的飞行器相对于地面坐标系的运动变量进行描述,通过隔离实际飞行中难以观测到的风干扰影响,基于高阶泰勒展开多元函数变量分解理论,构建仅与无人机自身特性相关、不同风况条件下通用的固定翼无人机空气动力共性基函数解析模型,结合在线辨识的风干扰系数函数,进而实现对飞行器飞行过程中气动力(矩)的预测。研究表明文章发展的“元飞行”气动模型可以良好地预测未知风况下固定翼无人机的气动力(矩),为实时空气动力学建模的实现奠定了良好基础。

无人机智能巡检在风电光伏故障检测中的实践应用研究

随着现代科学技术的迅速发展,无人机在各领域中的应用日益普遍,依托其灵活轻便、功能丰富、适应性强、成本较低等优势,能够完成各类相对复杂的任务,应用前景极为广阔。在当前的风电光伏领域中,无人机设备的应用也越来越多,无人机智能巡检便是其中之一。据此,文章将立足于无人机智能巡检,探讨其在实践应用中的模式及特点,并通过风电光伏故障检测实践,构建现代化的风电光伏智能巡检模式,以推动电力行业的高效安全发展。

Spray drift characteristics test of unmanned aerial vehicle spray unit under wind tunnel conditions

Since the 2010s,unmanned aerial vehicle(UAV)sprayer was applied more and more widely for low-volume aerial pesticides spraying operations in China.However,droplets from the UAV sprayer have a higher drift risk due to more fine droplets sprayed and a higher flight height than ground sprayers.Study on UAV spray drift has been a new hot spot within the field of pesticide application technology.Most of previous studies used direct field methods for spray drift,but the meteorological conditions in field were unstable and uncontrollable,and drift research under an actual operation state in wind tunnel has not been reported.Therefore,25 treatments of wind tunnel measurements and droplets spectrum tests of 10 models of nozzles were conducted to explore the influence factor on spray drift characteristics of UAV chemicals application in this study.A spray unit with a rotor of UAV was innovatively installed in wind tunnel,and the airstream from the wind tunnel was regarded as the relative moving natural wind to simulate the flight status.The airborne and the sediment spray drift was measured to study the effects of the nozzle type and size(flat fan,hollow cone and air-inclusion nozzles),flight speed,adjuvant(DRS-60,Y-20079,MF and G-611)and meteorological parameters(20°C&40%,20°C&80%,30°C&40%and 30°C&60%).The drift potential(DP)and the drift potential reduction percentage(DPRP)in vertical and horizontal directions were obtained for each test.Both nozzle type and size had an impact on the spray drift potential obviously by affecting the droplet size and the ratio of fine droplets,and the regression linear models between DPRPV/DPRPH and DV50,V75 were established(R2=0.934/0.925).Flight speed also had a significant effect on the spray drift characteristics,and reducing the flight speed could increase the DP effectively.Adding spray adjuvants could affect the DP under experimental meteorological parameters,and the anti-drift performance ranked in the order of DRS-60>MF>Y-20079>G-611.Recommendations were proposed in order to reduce the spray drift for UAV sprayer’s operation.These findings can contribute to provide guidelines and technical support for the wind tunnel spray drift tests of UAV and the field operation regulation of unmanned aerial PPP application.

Wind Estimation for UAV Based on Multi-sensor Information Fusion

Aiming at the requirements of accurate target positioning and autonomous capability for adapting to the environmental changes of unmanned aerial vehicle(UAV),a new method for wind estimation and airspeed calibration is proposed.The method is implemented to obtain both wind speed and wind direction based on the information from a GPS receiver,an air data computer and a magnetic compass,combining with the velocity vector triangle relationships among ground speed,wind speed and air speed.Considering the installation error of Pitot tube,cubature Kalman filter(CKF)is applied to determine proportionality calibration coefficient of true airspeed,thus improving the accuracy of wind field information further.The entire autonomous flight simulation is performed in a constant 2-D wind using a digital simulation platform for UAV.Simulation results show that the wind speed and wind direction can be accurately estimated both in straight line and in turning segment during the path tracking by using the proposed method.The measurement accuracies of the wind speed and wind direction are 0.62 m/s and2.57°,respectively.

Wind disturbance rejection control based on the dynamic parameters estimation of quadrotors UAV

The turbulence or gust in quadrotor flight environment causes drastic changes in the unmanned aerial vehicle(UAV)aerodynamic parameters.Especially,rotor thrust coefficient and reaction torque coefficient of the UAV encounter uncertainty fluctuation,which may undermine the control performance.A real-time estimation strategy for these aerodynamic parameters is proposed to improve the identification on the disturbance.First,the unscented Kalman filter(UKF)algorithm is used to estimate the UAV states and aerodynamic parameters.Then,a double-loop structure,consisting of position and attitude,is designed for the trajectory tracking control.In the outer loop,a proportional-derivative controller is adopted to carry out position tracking and provide Euler angle references for the inner loop,called attitude controller.Moreover,the attitude controller is designed using an inverse dynamic technique.The main contribution of this study is to propose a joint estimation on the aerodynamic parameters with wind disturbance as well as the UAV states.This strategy plays an important role in refining time-varying parameters of wind disturbance.A number of simulations are executed to verify the effectiveness of the proposed method.

Concept of Spinsonde for Multi-Cycle Measurement of Vertical Wind Profile of Tropical Cyclones

Tropical cyclones and cyclogenesis are active areas of research. Chute-operated dropsondes are capable of acquiring high resolution vertical wind profile of tropical cyclones. This work proposes a chute-free vertical retardation technique (termed as spinsonde) that can accurately measure vertical wind speed profile. Unlike the expendable dropsondes, the spinsonde allows multi-cycle measurement to be performed within a single flight. Proof of principle is demonstrated via simulation and results indicate that the ground speed correlates with the wind speeds to within ±5 km·h-1. This technique reduces flying weight and increases payload capacity by eliminating bulky chutes. Maximum cruising speed (VH) achieved by the spinsonde UAV is 368 km·h-1.

基于无人机航拍的近地风场类别确定方法

应用无人机航拍城市地区地面的照片,通过对照片进行识别可快速获取地面建筑物信息,进而有效地获得测区内地貌状况并且实现参数化.通过建立地面粗糙度Z0与地面粗糙度指数α的对应关系可以确定该地区近地风场类别,同时应用无人机搭载风速仪对该地区的风场和风剖面进行实测并通过分析获得了该地区的近地风场类别,进而对采用两种方法获得的近地风场类别识别结果进行了比较.结果表明,通过这两种方法判定的场地类别一致,且相对误差在5%以内.该研究实现了依据实际地貌判定同目标建筑相关的风场类别,所用方法具有广泛的适用性,研究结果可为城市地区的建筑抗风设计提供新思路.

随机风速风向对无人机地面风险作用效果研究

为准确计算无人机地面坠毁后造成的伤人风险值,考虑空域环境内风对无人机坠落过程的影响,尤其是随机风速与风向对无人机地面坠毁位置的作用效果,并引入二阶标准模型定义无人机坠落过程,建立随机风速与风向作用效果模型,将风的作用输入到无人机坠落全过程,兼以真实运行场景参数、无人机自身运行参数,开展多因素作用下的地面风险评估,重点探讨风速、风向对地面不同区域内人群带来的风险作用,进而得出更加可靠真实风险评估结果。结果表明:环境内风的作用会对无人机地面坠毁位置产生显著影响,最终使得地面风险分布极不均匀,且风险数值远高于民航有人机的安全标准,因此,无人机不适宜在某些较为复杂的城市环境下运行。

基于神经网络的旋翼无人机空中原位风速反演

旋翼无人机空气动力学模型能够克服无人机旋翼下洗气流的影响,相比携带传感器直接测风具有一定优势。空气动力学模型利用无人机自身的姿态数据可以直接计算得到风向,但是风速的计算还需要开展大量的风洞实验以及复杂的实体建模获取相关参数。为简化流程、规避参数获取过程中存在的误差,采用BP(back propagation)神经网络替代风洞实验和实体建模,研究无人机姿态同自然风速的关系。通过确定风速影响因子,分别建立以两个欧拉角为输入和以两个欧拉角计算得到的倾角为输入的旋翼无人机空中原位风速反演模型EUL-BP(euler back propagation)和INC-BP(incline back propagation)。以无人机悬停等高度风塔上超声风速仪观测自然风速为真值,比较反演模型EUL-BP和INC-BP发现,INC-BP增强了BP神经网络寻优过程的约束,反演效果较EUL-BP更优,其均方根误差大致为0.65 m/s,相关系数为0.86左右;比较反演模型结果与无人机机载自动气象站观测结果发现,当风力条件为三级及以下时,反演风速远优于携带传感器观测的风速。

无人机搭载宽带5G通信技术在海上作业中的应用

随着时代的发展,我国的科学技术水平明显提升,尤其是无人机技术,已广泛应用在各行各业中。同时,随着通信技术的持续发展,5G网络能够提供更加快速的数据传输支持,4K高清数据传输逐渐成为现实。基于此,在分析海上作业需求的基础上,分析了无人机搭载宽带5G通信技术在海上作业中的应用,同时进行了可用性测试,希望能够为相关研究提供理论支持。