无人机空中加油自主会合制导律研究

典型的自主会合制导律主要包括基于在线估计的制导律和无需在线估计的制导律两大类,其中在线估计具有计算量大,实现复杂的缺点。提出了一种无需在线估计的制导律,在此基础上,文章进行了改善,一是借鉴导弹中的带落角约束的比例导引律,实现了一种同时满足航向和纵向自主会合要求的制导律形式,简化了制导律设计;二是引入了相对距离反馈与速度反馈进行相对距离控制,避免了速度控制指令设计的复杂化和开环控制鲁棒性差的缺点。最后,通过一个仿真例子证明了这种制导律方案原理可行,具有一定的工程应用价值。     

面向无人机空中加油紧密编队的鲁棒控制方法

针对无人机空中加油紧密编队系统鲁棒控制问题,提出了一种基于障碍函数的自适应干扰观测器的分布式鲁棒编队控制方法。对固定翼无人机外环动力学模型进行转换,构造了具有非匹配和匹配扰动的二阶多体系统简化模型,并基于障碍函数设计了相应通道的自适应干扰观测器;利用邻机状态信息定义了相应的一致误差函数,在此基础上,基于编队系统通信拓扑结构,引入干扰补偿机制,开发了空中加油无人机紧密编队系统分布式鲁棒控制器,以实现理想的异构无人机编队跟踪控制性能。基于Lyapunov稳定性理论,分析了闭环系统的稳定性和收敛性。最后,通过将所提方法应用在由不同型号的1架加油机和2架受油机构成的编队系统上,进行数值仿真验证。所得到仿真结果与理论分析一致,验证了设计的干扰观测器和控制器的有效性。     

某小型无人机编队控制器设计及试飞验证

以某小型固定翼无人机作为研究平台,按前向、侧向和垂直方向3个通道设计僚机编队控制器.利用自动驾驶仪的航路飞行模态简化侧向通道编队控制器的设计,并采用在长机航向角发生较大变化时加入基于视线方位角的方法,使僚机保持编队精度.试验结果表明,所提出的编队算法是可用的,并能够很好地控制无人机的编队飞行精度.     

无人机自主编队制导律设计

自主编队是无人机集群作战的关键技术.提出了一种基于视线的三维无人机双机与多机自主编队方法.制导律采用横纵分离的经典PD控制方式进行设计,建立了加入制导律的双机、多机的质点相对运动学模型,通过求解该模型在平衡点处的雅克比矩阵的特征根,来判断制导律的稳定性.仿真结果表明:设计的制导律能有效导引无人机构成编队,并保持编队飞行.     

自主空中加油变质量无人机建模与控制

针对空中加油任务中无人作战飞机(UCAV)的位置保持问题,进行了变质量UCAV的动力学建模与控制律设计.综合考虑了燃油传输对UCAV质量、惯性矩阵和质心位置的影响,基于相对惯性系的状态变量,推导了UCAV的动力学方程.建立了一个简单的油箱模型来模拟加油过程,设计了H∞最优控制律来实现UCAV的位置保持.通过非线性仿真,分析了燃油传输带来的动力学影响,仿真结果验证了模型的有效性和控制律的性能.     

无人机编队飞行控制器设计

主要对两架无人机斜线编队控制进行研究,建立了相应的数学模型,并基于PI控制律分别设计了x,y两个方向的控制器,利用解析和数值计算两种方法解算.仿真结果表明,设计的控制器可以控制僚机跟随长机机动,保持原有的相对位置和姿态.     

无人机自主空中加油技术探究

作为提高无人机作战效能的有效手段,无人机自主空中加油技术近年来已成为了无人机研究领域的重要发展方向.本文在总结国外无人机自主空中加油技术发展的基础上,指出了基于"插头-锥管"的无人机自主空中加油的关键技术和发展方向,对于研究无人机空中加油技术具有一定的借鉴意义.     

无人机空中加油自主会合的制导与控制

针对无人机空中加油的自主会合问题,进行了相应制导律和非线性控制器的设计。通过改进的带角度约束的三维比例制导律实现对航向角的控制,以协调转弯的方式将航迹角指令转化为姿态角指令。基于无人机六自由度的动力学模型,针对无人机的姿态控制,采用时标分离的方法设计了慢子系统和快子系统,并对这两个子系统分别进行动态逆控制设计。同时,基于滑模控制的方法设计了满足自主会合要求的速度控制律。在保证无人机飞行稳定的基础上,实现了对控制和制导指令的精确跟踪。仿真结果表明,所设计的制导律和控制律能够实现无人机空中加油的自主会合,具有良好的动态特性。     

无人机软管式自主空中加油视觉导航技术

近年来,机器视觉技术的迅速发展给无人机自主空中加油提供了一种新思路,克服了传统GPS动态适应能力差的不足。基于双目视觉,提出了一种实用的无人机自主空中加油导航方案,并提出了一种利用深度学习进行检测跟踪配合几何约束进行位姿计算的技术。根据加油机和受油机距离的不同,将导航分为远端导航和近端导航。全程对加油锥套进行检测和跟踪,并在近端进行锥套位姿计算。实验结果表明,该算法满足加油的鲁棒性要求,稳定跟踪锁定目标距离范围大于40m。当与目标距离小于10m时,距离误差优于±10cm。说明本文提出的方法具有较强的应用前景。     

视觉辅助的无人机自主空中加油建模与仿真

为准确获得插头锥套式空中加油过程中无人机与锥套的相对位姿信息,提出了机器视觉辅助的插头锥套式无人机自主空中加油仿真方案,开发了基于Open CV,Simulink及Vega Prime视景仿真技术的闭环仿真系统.研究了机器视觉识别跟踪锥套的图像处理算法,利用Kalman滤波算法估计无人机与锥套的相对位姿.仿真结果表明,机器视觉算法可以准确识别跟踪锥套,滤波器状态估计的收敛速度较快,无人机姿态角变化范围较小,保证了插头锥套式无人机自主空中加油的平稳安全对接.     

非线性动态逆空中加油自主对接控制

为实现无人机空中加油自主对接控制,建立了尾流影响下的UAV六自由度模型。基于非线性动态逆,设计了空中加油自主对接控制律。在常规非线性动态逆控制律设计的基础上,改进了航迹、姿态、角速率和自动油门等回路。通过设计航迹跟踪控制律和动态逆自动油门,实现了对锥套位置的跟踪和对接;考虑协调转弯约束和爬升速率约束,在设计过程中以姿态角代替气流角,克服了气流角控制带来的幅值、速率过大的问题,使受油机的控制更加稳定。最后通过仿真,验证了动态逆自主对接控制律的有效性。     

A guidance law for UAV autonomous aerial refueling based on the iterative computation method

The rendezvous and formation problem is a significant part for the unmanned aerial vehicle（UAV） autonomous aerial refueling（AAR） technique. It can be divided into two major phases： the long-range guidance phase and the formation phase. In this paper, an iterative computation guidance law（ICGL） is proposed to compute a series of state variables to get the solution of a control variable for a UAV conducting rendezvous with a tanker in AAR. The proposed method can make the control variable converge to zero when the tanker and the UAV receiver come to a formation flight eventually. For the long-range guidance phase, the ICGL divides it into two sub-phases： the correction sub-phase and the guidance sub-phase. The two sub-phases share the same iterative process. As for the formation phase, a velocity coordinate system is created by which control accelerations are designed to make the speed of the UAV consistent with that of the tanker.The simulation results demonstrate that the proposed ICGL is effective and robust against wind disturbance.     

Drogue detection for autonomous aerial refueling based on convolutional neural networks

Drogue detection is a fundamental issue during the close docking phase of autonomous aerial refueling(AAR). To cope with this issue, a novel and effective method based on deep learning with convolutional neural networks(CNNs) is proposed. In order to ensure its robustness and wide application, a deep learning dataset of images was prepared by utilizing real data of ‘‘Probe and Drogue" aerial refueling, which contains diverse drogues in various environmental conditions without artificial features placed on the drogues. By employing deep learning ideas and graphics processing units(GPUs), a model for drogue detection using a Caffe deep learning framework with CNNs was designed to ensure the method's accuracy and real-time performance. Experiments were conducted to demonstrate the effectiveness of the proposed method, and results based on real AAR data compare its performance to other methods, validating the accuracy, speed, and robustness of its drogue detection ability.     

空中加油变质量建模与干扰补偿控制

为抑制空中加油给飞机带来的变质量影响,将质量的变化等效为对飞机的干扰力和干扰力矩,建立了变质量飞机的一般动力学模型,并经过小扰动线性化得到飞机带干扰的纵向状态方程.采用比例积分观测器(PIO)对干扰进行观测,基于观测值设计了补偿控制器以实现对变质量干扰的抑制.以受油机为例进行计算机仿真,结果表明,该模型有效地反映了变质量受油机的动力学特性,干扰补偿控制器能够实现对变质量受油机的精确控制.     

软式空中加油受油机头波数值仿真分析

针对软式空中加油对接过程中受油机头波加剧软管锥套飘摆、降低对接成功率的问题,建立了受油机三维模型,利用Delaunay方法自下向上生成非结构网格.通过计算ONERA M6三维翼型表面压力分布和压力系数,验证了三维Navier-Stokes方程和SST k-ω湍流模型的有效性.在此基础上对不同飞行条件下受油机头波进行静态数值计算,分析了头波随马赫数和迎角的变化规律,并通过仿真解释了头波影响下软管锥套的飘摆原因,预测了对接时锥套的运动趋势.     

Real-time drogue recognition and 3D locating for UAV autonomous aerial refueling based on monocular machine vision

Drogue recognition and 3D locating is a key problem during the docking phase of the autonomous aerial refueling(AAR). To solve this problem, a novel and effective method based on monocular vision is presented in this paper. Firstly, by employing computer vision with red-ring-shape feature, a drogue detection and recognition algorithm is proposed to guarantee safety and ensure the robustness to the drogue diversity and the changes in environmental conditions, without using a set of infrared light emitting diodes(LEDs) on the parachute part of the drogue. Secondly, considering camera lens distortion, a monocular vision measurement algorithm for drogue 3D locating is designed to ensure the accuracy and real-time performance of the system,with the drogue attitude provided. Finally, experiments are conducted to demonstrate the effectiveness of the proposed method. Experimental results show the performances of the entire system in contrast with other methods, which validates that the proposed method can recognize and locate the drogue three dimensionally, rapidly and precisely.     

Modeling and simulation of bow wave effect in probe and drogue aerial refueling

In a probe and drogue aerial refueling system, the bow wave of the receiver aircraft will produce a strong aerodynamic effect on the drogue once the receiver follows the drogue at a close distance. It is a major difficulty of docking control in the probe and drogue refueling. This paper analyses the bow wave effect and presents a simple method to model it. Firstly, the inviscid flow around the receiver is modeled based on the stream function defined by basic stream singularities.Secondly, a correction function is developed to eliminate the error caused by the absence of air viscosity. Then, the aerodynamic coefficients are used to calculate the induced aerodynamic force on the drogue. The obtained model is in an analytical form that can be easily applied to the controller design and the real-time simulations. In the verification part, computational fluid dynamics(CFD)simulation tests are conducted to validate the obtained flow fields and aerodynamic forces. Finally,the modeling method is applied to an F-16 receiver aircraft in a previously developed autonomous aerial refueling simulation system. The simulations results are analyzed and compared with the NASA flight-test data, which demonstrates the effectiveness of the proposed method.     

CamShift在加油锥套识别跟踪中的应用

针对插头锥套式自主空中加油过程中加油锥套的识别跟踪问题,提出了一种基于Cam Shift的视觉识别跟踪算法。选取加油锥套跟踪视觉特征,将RGB空间图像转换到HSV色彩空间,并采用自适应阈值算法分割图像。运用最小二乘椭圆拟合算法解算锥套在图像中的中心点坐标;根据目标像素位置变换速度,对Mean Shift算法的目标搜索窗宽进行自适应修正;定义基于巴氏系数的阈值函数,处理锥套被遮挡的情况;将VC与Open CV相结合,设计了加油锥套视觉跟踪软件,对锥套位置进行实时解算和显示。试验结果表明,该算法可达到毫米级精度,满足自主空中加油视觉导航的技术要求。