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.     

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。     

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.     

无人机空中加油自主编队控制器设计

针对自主空中加油(AAR)任务中的飞行器编队形成问题,提出了一个完整的自主控制器方案。采用基于视线的编队制导律控制队形,产生制导指令。针对加油编队过程中产生的模型误差和尾涡扰动等不确定性,基于RBF神经网络和自适应Backstepping方法,设计了UAV姿态和速度非线性控制律来在线逼近和补偿不确定性,保证系统的鲁棒性和稳定性。使用协调转弯方式将航迹角指令转换为姿态指令,以实现控制律对航迹角指令的精确跟踪。最后,仿真结果验证了制导律和控制律的有效性。     

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。     

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.     

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。     

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。     

无人机自主空中加油技术新进展

近年来,美国多家研究机构和防务公司一直在推进无人机的自主空中加油（AAR）技术的实用化研究。GE公司于近期公布了他们的AAR研究计划,其激光导航AAR系统（AARLNS）以精度高、稳定性好、抗电磁干扰能力强等特点引起业界的普遍关注。     

无人作战飞机空中加油建模与近距机动控制律设计

针对无人作战飞机(UCAV)空中加油时存在加油机尾流干扰导致相对位置难以保持的问题,基于等效气动效应法建立了UCAV动力学模型,并设计了近距机动最优飞行控制律.将加油机尾流对UCAV的影响等效为平均风速度和风梯度,计算出附加于UCAV的诱导力系数和诱导力矩系数,建立了含尾流扰动的受油机模型.以位置跟踪误差的积分为增广状态,基于加权二次型性能指标设计了近距机动最优飞行控制律.仿真结果表明,UCAV模型能真实地体现尾流对受油机的影响,并通过设计的近距机动控制律可有效实现对加油机相对位置的精确跟踪.     

硬式空中加油装置运动建模与仿真研究

针对由加油机和硬式加油伸缩管构成的硬式空中加油多体动力学系统,在已有的加油机运动仿真模型的基础上,考虑加油机的尾流场扰动作用,采用基于拉格朗日方程的速度传递矩阵法,建立了系统运动仿真模型。通过运动仿真,对伸缩管的动态特性和系统的紊流扰动响应特性进行了研究。仿真结果表明,硬管的动态响应特性较差、阻尼偏小,且俯仰运动与偏航运动耦合,需控制系统予以改善并实现解耦操纵;轻微的紊流对硬管的姿态具有较明显的扰动作用,通过稳定加油机的航迹,能够显著改善硬式加油装置的抗紊流特性。     

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.     

Modeling and simulation of a time-varying inertia aircraft in aerial refueling

Studied in this paper is dynamic modeling and simulation application of the receiver aircraft with the time-varying mass and inertia property in an integrated simulation environment which includes two other significant factors, i.e., a hose–drogue assembly dynamic model with the variable-length property and the wind effect due to the tanker's trailing vortices. By extending equations of motion of a fixed weight aircraft derived by Lewis et al., a new set of equations of motion for a receiver in aerial refueling is derived. The equations include the time-varying mass and inertia property due to fuel transfer and the fuel consumption by engines, and the fuel tanks have a rectangle shape rather than a mass point. They are derived in terms of the translational and rotational position and velocity of the receiver with respect to an inertial reference frame. A linear quadratic regulator(LQR) controller is designed based on a group of linearized equations under the initial receiver mass condition. The equations of motion of the receiver with a LQR controller are implemented in the integrated simulation environment for autonomous approaching and station-keeping of the receiver in simulations.     

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.