Modeling Method and Control Strategy for Hose-Drogue Aerial Refueling System

Conventional method for hose-drogue model of aerial refueling system is known to be complex due to the flexible body of hose.And as reported,drogues are unstable in atmospheric turbulence,which greatly decreases docking success rates.This paper proposes a dynamic model for a hose-drogue aerial refueling system based on Kane equation and rigid multi-body dynamics,and analyzes its performance.Furthermore,the nonlinear dynamic model is linearized at the equilibrium point and simplified from full order to 2 nd order.Based on the simplified 2 nd order model,active control strategies,including proportion integral derivative(PID)and liner quadratic regulator(LQR)control laws,are designed to inhibit the pendulum movement of drogue due to,atmospheric turbulences.Numerical simulation results show the significant correctness of the proposed dynamic model by steady-state drag and balance position of drogue when the tanker flights under different conditions.Moreover,the steady state position error varies within 1 cm,thanks to either controller,when the drogue suffers from moderate-level atmospheric turbulences.Further,the PID controller exhibits better control effect and higher control precision than LQR controller.

Guidance and Control for UAV Aerial Refueling Docking Based on Dynamic Inversion with L_1 Adaptive Augmentation

The guidance and control for UAV aerial refueling docking based on dynamic inversion with L1 adaptive augmentation is studied.In order to improve the tracking performance of UAV aerial refueling docking,aguidance algorithm is developed to satisfy the tracking requirement of position and velocity,and it generates the UAV flight control loop commands.In flight control loop,based on the 6-DOF nonlinear model,the angular rate loop and the attitude loop are separated based on time-scale principle and the control law is designed using dynamic inversion.The throttle control is also derived from dynamic inversion method.Moreover,an L1 adaptive augmentation is developed to compensate for the undesirable effects of modeling uncertainty and disturbance.Nonlinear digital simulations are carried out.The results show that the guidance and control system has good tracking performance and robustness in achieving accurate aerial refueling docking.

Numerical Analysis of Refueling Drogue Oscillation During Refueling Docking

Refueling docking at different velocities is simulated by using computational fluid dynamics(CFD)method.The Osher scheme and S-A turbulence model are used to solve the compressible Navier-Stokes equations,and the Delaunay mapping dynamic grid method is also employed.All the numerical results show that the velocity of refueling docking is very important for aerial refueling.When the velocity is lower than 3m/s,the refueling drogue will move upward with obvious cycle staggering,while moving upward with slight cycle staggering at the speed of3m/s.The results can be referenced by aerial refueling design.

LQR Integrated with Fuzzy Control for Aerial Refueling Autopilot

Linear Quadratic Regulator （LQR） is modem linear control that is suitable for multivariable state feedback and is known to yield good performance for linear systems or for nonlinear systems where the nonlinear aspects are presented. The fuzzy control is known to have the ability to deal with nonlinearities without having to use advanced mathematics. The LQR integrated fuzzy control （LQRIFC） simultaneously makes use of the good performance of LQR in the region close to switching curve, and the effectiveness of fuzzy control in region away from switching curve. A new analysis of the fuzzy system behavior presented helps to make possible precise integration of LQR features into fuzzy control. The LQRIFC is verified by simulation to suppress the uncertainty instability more effectively than the LQR besides minimizing the time of the mission proposed.

Modeling and Simulation for Refueling Boom and Receiver inCoupled Mode

In coupled mode,the major problem of boom refueling system is undesirable nozzle loads.An automated load alleviation system(ALAS)is needed to alleviate nozzle loads.In order to simulate dynamic of the system and to validate ALAS,dynamic model is developed.Two models are established,which are the static model and the moving model,named after the two relative states between the fixed boom and the extension boom.Kane method is employed as main method considering system′s multi-body characteristics.D′Alembert′s principle is used to calculate nozzle loads.Simulation is conducted to research the effects of position disturbance and velocity disturbance on nozzle loads.Results indicate that position disturbance plays a more significant role in inducing nozzle loads.A fuzzy control law based ALAS is validated using the formulated model.It is concluded that this model can simulate system dynamic and validate ALAS.

Progress in modeling and control of probe-and-drogue autonomous aerial refueling

By refueling aircraft while they are in flight,aerial refueling is an efficient technique to extend their endurance and range.Autonomous Aerial Refueling(AAR)is anticipated to be used to complete aerial refueling for unmanned aircraft.There are three aerial refueling methods:the Probe-and-Drogue Refueling(PDR)refueling method,the flying-boom refueling method,and the boom-drogue-adapter refueling method.The paper considers the PDR approach,the most challenging of the three,because the flexible hose-drogue assembly has fast dynamics and is susceptible to various kinds of winds,which makes the probe docking with the drogue difficult.PDR is divided into four phases,namely the rendezvous phase,joining phase,refueling phase,and reform phase,with the refueling phase being the most crucial.The controller design faces the greatest challenge during the docking control of the refueling phase since it calls for a high level of safety,precision,and efficiency.As a result,the modeling and control issues encountered during the refueling phase are typical and difficult.The fundamental idea of AAR is presented in the paper first,after which the characteristics and requirements of AAR are outlined.The progress in modeling and control techniques for the AAR’s refueling phase is then systematically reviewed.Finally,potential future work for high safety,precision,and efficiency requirements is examined and suggested.

Unmanned autonomous air-to-air refueling intelligent docking technology

Unmanned autonomous Air-to-Air Refueling(AAR)capability is the key guarantee to support the distant-field,high-intensity and durable operations of the penetration counterair combat system.In the future,the long-range unmanned reconnaissance and attack platform can reach the maximum flight range requirement through AAR.At present,large transport aircraft platforms in China are still equipped with probe-and-drogue systems,and the refueling mode is gradually changing from manned to unmanned autonomous operation.The docking process is the riskiest and most important part,and there are strict safety,precision,and efficiency requirements for refueling operation,especially during close-distance docking and formation maintenance phases.In this paper,five issues that need to be solved to achieve autonomous AAR docking are summarized.On this basis,five key technology development needs are proposed to solve these engineering issues.Finally,some prospects are given.

Aerial refueling scheduling of multi-receiver and multi-tanker under spatial-temporal constraints for forest firefighting

Forest fires pose a significant threat to human life and property,so the utilization of unmanned aircraft systems provides new ways for forest firefighting.Given the constrained load capacities of these aircraft,aerial refueling becomes crucial to extend their operational time and range.In order to address the complexities of firefighting missions involving multi-receiver and multi-tanker deployed from various airports,first,a fuel consumption calculation model for aerial refueling scheduling is established based on the receiver path.Then,two distinct methods,including an integrated one and a decomposed one,are designed to address the challenges of establishing refueling airspace and allocating tasks for tankers.Both methods aim to optimize total fuel consumption of the receivers and tankers within the aerial refueling scheduling framework.The optimization problem is established as nonlinear optimization models along with restrictions.The integrated method seamlessly combines refueling rendezvous point scheduling and tanker task allocation into unified process.It has a complete solution space and excels in optimizing total fuel consumption.The decomposed method,through the separation of rendezvous point scheduling and task allocation,achieves a reduced computational complexity.However,this comes at the cost of sacrificing optimality by excluding specific feasible solutions.Finally,numerical simulations are carried out to verify the feasibility and effectiveness of the proposed methods.These simulations yield insights crucial for the practical engineering application of both the integrated and decomposed methods in real-world scenarios.This comprehensive approach aims to enhance the efficiency of forest firefighting operations,mitigating the risks posed by forest fires to human life and property.

Drogue detection for autonomous aerial refueling via hybrid pigeon-inspired optimized color opponent and saliency aggregation

Drogue detection is one of the challenging tasks in autonomous aerial refueling due to the requirement for accuracy and rapidity.Saliency detection based on image intrinsic cues can achieve fast detection,but with poor accuracy.Recent studies reveal that optimization-based methods provide accurate and quick solutions for saliency detection.This paper presents a hybrid pigeon-inspired optimization method,the optimized color opponent,that aims to adjust the weight of color opponent channels to detect the drogue region.It can optimize the weights in the selected aerial refueling scene offline,and the results are applied for drogue detection in the scene.A novel algorithm aggregated by the optimized color opponent and robust background detection is presented to provide better precision and robustness.Experimental results on benchmark datasets and aerial refueling images show that the proposed method successfully extracts the saliency region or drogue and exhibits superior performance against the other saliency detection methods with intrinsic cues.The algorithm designed in this paper is competent for the drogue detection task of autonomous aerial refueling.

Vehicular volatile organic compounds losses due to refueling and diurnal process in China: 2010–2050

Volatile organic compounds（VOCs） are crucial to control air pollution in major Chinese cities since VOCs are the dominant factor influencing ambient ozone level, and also an important precursor of secondary organic aerosols. Vehicular evaporative emissions have become a major and growing source of VOC emissions in China. This study consists of lab tests, technology evaluation, emissions modeling, policy projections and cost-benefit analysis to draw a roadmap for China for controlling vehicular evaporative emissions. The analysis suggests that evaporative VOC emissions from China＇s light-duty gasoline vehicles were approximately 185,000 ton in 2010 and would peak at 1,200,000 ton in 2040 without control. The current control strategy implemented in China, as shown in business as usual（BAU） scenario, will barely reduce the long-term growth in emissions. Even if Stage II gasoline station vapor control policies were extended national wide（BAU ＋ extended Stage II）, there would still be over 400,000 ton fuel loss in 2050. In contrast, the implementation of on-board refueling vapor recovery（ORVR） on new cars could reduce 97.5% of evaporative VOCs by 2050（BAU ＋ ORVR/BAU ＋ delayed ORVR）. According to the results, a combined Stage II and ORVR program is a comprehensive solution that provides both short-term and long-term benefits. The net cost to achieve the optimal total evaporative VOC control is approximately 62 billion CNY in 2025 and 149 billion CNY in 2050.

Dynamic modeling of a hose-drogue aerial refueling system and integral sliding mode backstepping control for the hose whipping phenomenon

Dynamic modeling of a hose-drogue aerial refueling system（HDARS） and an integral sliding mode backstepping controller design for the hose whipping phenomenon（HWP） during probe-drogue coupling are studied. Firstly, a dynamic model of the variable-length hose-drogue assembly is built for the sake of exploiting suppression methods for the whipping phenomenon.Based on the lumped parameter method, the hose is modeled by a series of variable-length links connected with frictionless joints. A set of iterative equations of the hose＇s three-dimensional motion is derived subject to hose reeling in/out, tanker motion, gravity, and aerodynamic loads accounting for the effects of steady wind, atmospheric turbulence, and tanker wake. Secondly,relying on a permanent magnet synchronous motor and high-precision position sensors, a new active control strategy for the HWP on the basis of the relative position between the tanker and the receiver is proposed. Considering the strict-feedback configuration of the permanent magnet synchronous motor, a rotor position control law based on the backstepping method is designed to insure global stability. An integral of the rotor position error and an exponential sliding mode reaching law of the current errors are applied to enhance control accuracy and robustness. Finally,the simulation results show the effectiveness of the proposed model and control laws.

Vision-based Estimation of Relative Pose in Autonomous Aerial Refueling

The lack of autonomous aerial refueling capabilities is one of the greatest limitations of unmanned aerial vehicles. This paper discusses the vision-based estimation of the relative pose of a tanker and unmanned aerial vehicle, which is a key issue in autonomous aerial refueling. The main task of this paper is to study the relative pose estimation for a tanker and unmanned aerial vehicle in the phase of commencing refueling and during refueling. The employed algorithm includes the initialization of the orientation parameters and an orthogonal iteration algorithm to estimate the optimal solution of rotation matrix and translation vector. In simulation experiments, because of the small variation in the rotation angle in aerial refueling, the method in which the initial rotation matrix is the identity matrix is found to be the most stable and accurate among methods. Finally, the paper discusses the effects of the number and configuration of feature points on the accuracy of the estimation results when using this method.

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 condi- tions, without using a set of infrared light emitting diodes （LEDs） on the parachute part of the dro- gue. 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 effective- ness 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 vis- cosity. 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.

Verification of monocular and binocular pose estimation algorithms in vision-based UAVs autonomous aerial refueling system

With the high focus on autonomous aerial refueling(AAR), it becomes increasingly urgent to design efficient methods or algorithms for solving the AAR problems in complicated aerial environments. A vision-based technology for AAR is developed in this paper, and five monocular and binocular visual algorithms for pose estimation of the unmanned aerial vehicles(UAVs) are adopted and verified in this AAR system. The real-time on-board vision system is also designed for precise navigation in the UAVs docking phase. A series of out-door comparative experiments for different pose estimation algorithms are conducted to verify the feasibility and accuracy of the vision algorithms in AAR.

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.

Docking control for probe-drogue refueling: An additive-state-decomposition-based output feedback iterative learning control method

Designing a controller for the docking maneuver in Probe-Drogue Refueling(PDR) is an important but challenging task, due to the complex system model and the high precision requirement.In order to overcome the disadvantage of only feedback control, a feedforward control scheme known as Iterative Learning Control(ILC) is adopted in this paper.First, Additive State Decomposition(ASD) is used to address the tight coupling of input saturation, nonlinearity and the property of Non Minimum Phase(NMP) by separating these features into two subsystems(a primary system and a secondary system).After system decomposition, an adjoint-type ILC is applied to the Linear Time-Invariant(LTI) primary system with NMP to achieve entire output trajectory tracking, whereas state feedback is used to stabilize the secondary system with input saturation.The two controllers designed for the two subsystems can be combined to achieve the original control goal of the PDR system.Furthermore, to compensate for the receiverindependent uncertainties, a correction action is proposed by using the terminal docking error,which can lead to a smaller docking error at the docking moment.Simulation tests have been carried out to demonstrate the performance of the proposed control method, which has some advantages over the traditional derivative-type ILC and adjoint-type ILC in the docking control of PDR.

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 con- troller are implemented in the integrated simulation environment for autonomous approaching and station-keeping of the receiver in simulations.

Suggested closed-loop response characteristics for tanker in aerial refueling via mission-oriented evaluation

The flight control law design for tanker should ensure that the closed-loop response can meet the aerial refueling mission requirements. In order to reveal the movement characteristics of the tanker and the handling characteristics of the pilot in aerial refueling, the flight path capture and hold under gust disturbance task is designed as the demonstration maneuver mission to evaluate the flying qualities for tanker in aerial refueling task, which is based on the design requirements of maneuvering tasks used in mission-oriented flying qualities assessment. By analyzing the flight path tracking and holding requirements of the tanker in aerial refueling mission, the relevant parameters that reflect the response characteristics of the tanker in pitch and roll axes are put forward. The ground flight simulation test based on mission-oriented flight quality assessment is conducted, and the test pilot's assessment results based on Cooper-Harper rating and PIO scales are obtained for different flight control law configurations. The suggested requirements of the closed-loop response characteristics of the pitch and roll axes of the tanker are put forward, which can be specifications for the aerial refueling mode flight control design of tanker.

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.