Real-time and accurate drogue pose measurement during docking is basic and critical for Autonomous Aerial Refueling(AAR).Vision measurement is the best practicable technique,but its measurement accuracy and robustness...Real-time and accurate drogue pose measurement during docking is basic and critical for Autonomous Aerial Refueling(AAR).Vision measurement is the best practicable technique,but its measurement accuracy and robustness are easily affected by limited computing power of airborne equipment,complex aerial scenes and partial occlusion.To address the above challenges,we propose a novel drogue keypoint detection and pose measurement algorithm based on monocular vision,and realize real-time processing on airborne embedded devices.Firstly,a lightweight network is designed with structural re-parameterization to reduce computational cost and improve inference speed.And a sub-pixel level keypoints prediction head and loss functions are adopted to improve keypoint detection accuracy.Secondly,a closed-form solution of drogue pose is computed based on double spatial circles,followed by a nonlinear refinement based on Levenberg-Marquardt optimization.Both virtual simulation and physical simulation experiments have been used to test the proposed method.In the virtual simulation,the mean pixel error of the proposed method is 0.787 pixels,which is significantly superior to that of other methods.In the physical simulation,the mean relative measurement error is 0.788%,and the mean processing time is 13.65 ms on embedded devices.展开更多
Recovery is a crucial supporting process for carrier aircraft,where a reasonable landing scheduling is expected to guide the fleet landing safely and quickly.Currently,there is little research on this topic,and most o...Recovery is a crucial supporting process for carrier aircraft,where a reasonable landing scheduling is expected to guide the fleet landing safely and quickly.Currently,there is little research on this topic,and most of it neglects potential influence factors,leaving the corresponding supporting efficiency questionable.In this paper,we study the landing scheduling problem for carrier aircraft considering the effects of bolting and aerial refueling.Based on the analysis of recovery mode involving the above factors,two types of primary constraints(i.e.,fuel constraint and wake interval constraint)are first described.Then,taking the landing sequencing as decision variables,a combinatorial optimization model with a compound objective function is formulated.Aiming at an efficient solution,an improved firefly algorithm is designed by integrating multiple evolutionary operators.In addition,a dynamic replanning mechanism is introduced to deal with special situations(i.e.,the occurrence of bolting and fuel shortage),where the high efficiency of the designed algorithm facilitates the online scheduling adjustment within seconds.Finally,numerical simulations with sufficient and insufficient fuel cases are both carried out,highlighting the necessity to consider bolting and aerial refueling during the planning procedure.Simulation results reveal that a higher bolting probability,as well as extra aerial refueling operations caused by fuel shortage,will lead to longer recovery complete time.Meanwhile,due to the strong optimum-seeking capability and solution efficiency of the improved algorithm,adaptive scheduling can be generated within milliseconds to deal with special situations,significantly improving the safety and efficiency of the recovery process.An animation is accessible at bilibili.com/video/BV1QprKY2EwD.展开更多
Driven by the global“dual-carbon”goals,hydrogen fuel cell electric vehicles(FCEVs)are being rapidly promoted as a zero-emission transportation solution.However,their large-scale application is constrained by issues ...Driven by the global“dual-carbon”goals,hydrogen fuel cell electric vehicles(FCEVs)are being rapidly promoted as a zero-emission transportation solution.However,their large-scale application is constrained by issues such as inefficient operation,poor information flow between vehicles and stations,and potential safety hazards,which are caused by insufficient intelligence of hydrogen refueling stations.This study aims to address these problems by deeply integrating Cellular Vehicle-to-Everything(C-V2X)technology with hydrogen refueling stations,thereby building a safe,efficient,and low-carbon hydrogen energy application ecosystem to promote the global transition to zero-carbon transportation.Firstly,through literature review and technical analysis,this study expounds on the core technologies and process flows of current hydrogen refueling stations,aswell as the technical architecture and development evolution of C-V2X technology.Then,based on the analysis of relevant literature,it proposes a“vehicle-road-station-cloud”collaborative architecture that integrates C-V2X with hydrogen refueling stations.Combined with 5G communication and big data technologies,it elaborates on the implementation path for achieving real-time data interaction among hydrogen refueling stations,hydrogen-powered vehicles,and road infrastructure.This interconnection mode enables hydrogen refueling stations to obtain real-time information of surrounding vehicles,which plays an important role in building a safe,efficient,and low-carbon hydrogen energy application ecosystem and promoting the global transition to zero-carbon transportation.Finally,the future development prospects and potential of this scheme are put forward.展开更多
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 ...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.展开更多
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 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.展开更多
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,aeria...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.展开更多
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 poo...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.展开更多
Autonomous aerial refueling technology is gaining increasing attention to enhance aircraft combat capabilities.Current research on autonomous refueling focuses mainly on flight control laws,with little attention to th...Autonomous aerial refueling technology is gaining increasing attention to enhance aircraft combat capabilities.Current research on autonomous refueling focuses mainly on flight control laws,with little attention to the automation of refueling pipes.This leads to high demands on control law performance and navigation accuracy,making it difficult to ensure reliability.To address this,we propose a robotic arm system capable of automatic docking during the flexible aerial refueling process.The system uses a conical kinematic space configuration,offering enhanced stability and impact resistance.The frame-type structure achieves a lightweight design.Additionally,we establish a single-objective optimization model for the connecting rod dimensions and apply a genetic algorithm(GA)for their optimization.We also propose a trajectory-fitting calibration theory based on the robotic arm's special configuration and complete its movement accuracy calibration using a laser tracker.This calibration method reduces the robotic arm's motion error by 71%,achieving an absolute positioning accuracy better than 3.5 mm,which meets the requirements for autonomous aerial refueling.In summary,this research presents a hybrid robotic arm that meets automatic docking requirements,offering a new approach to autonomous aerial refueling.展开更多
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,...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.展开更多
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 ...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.展开更多
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 th...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.展开更多
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 aeria...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.展开更多
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 diffi...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.展开更多
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 disadvan...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.展开更多
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 netw...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.展开更多
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 significan...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.展开更多
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 a...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.展开更多
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 docki...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.展开更多
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 algo...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.展开更多
Hydrogen is starting to be mentioned as an alternative fuel to replace the fossil fuel in future transportation applications due to its characteristics of zero greenhouse gas emission and high energy efficiency. Befor...Hydrogen is starting to be mentioned as an alternative fuel to replace the fossil fuel in future transportation applications due to its characteristics of zero greenhouse gas emission and high energy efficiency. Before hydrogen fuel and its facilities can be introduced to the public, relevant safety issues and its hazards must be assessed in order to avoid any chance of injury or loss. While a traditional risk assessment has difficulty in prioritizing the risk of failure modes, this paper proposes a new fuzzy-based risk evaluation technique which uses fuzzy value to prioritize the risk of various scenarios. In this study, the final risk of each failure modes was prioritized by using the MATLAB fuzzy logic tool box with a combination of two assessments. The first assessment was concerned with the criteria which affected the actual probability of occurrence. This assessment considered the availability of the standard that was applied to prevent the likelihood of the scenario occurring. On the other hand, the second assessment was focused on evaluating the consequence of the failure by taking into account the availability of detection and the complexity of the failure rather than only the severity of the scenarios. A total of 87 failure scenarios were identified using failure modes and effect analysis (FMEA) procedures on hydrogen refueling station models. Fuzzy-based assessments were performed through risk prioritizing various failure scenarios with a fuzzy value (0 to 1) and risk level (low, medium, and high) while a traditional risk assessment approach presented the risks only in forms of level (low, medium, and/or high). Availability of the fuzzy value enabled further prioritizing on the risk results that fell in the same level of risk. This study concluded that fuzzy-based risk evaluation is able to further prioritize the decisions when compared with a traditional risk assessment method.展开更多
基金supported by the National Science Fund for Distinguished Young Scholars,China(No.51625501)Aeronautical Science Foundation of China(No.20240046051002)National Natural Science Foundation of China(No.52005028).
文摘Real-time and accurate drogue pose measurement during docking is basic and critical for Autonomous Aerial Refueling(AAR).Vision measurement is the best practicable technique,but its measurement accuracy and robustness are easily affected by limited computing power of airborne equipment,complex aerial scenes and partial occlusion.To address the above challenges,we propose a novel drogue keypoint detection and pose measurement algorithm based on monocular vision,and realize real-time processing on airborne embedded devices.Firstly,a lightweight network is designed with structural re-parameterization to reduce computational cost and improve inference speed.And a sub-pixel level keypoints prediction head and loss functions are adopted to improve keypoint detection accuracy.Secondly,a closed-form solution of drogue pose is computed based on double spatial circles,followed by a nonlinear refinement based on Levenberg-Marquardt optimization.Both virtual simulation and physical simulation experiments have been used to test the proposed method.In the virtual simulation,the mean pixel error of the proposed method is 0.787 pixels,which is significantly superior to that of other methods.In the physical simulation,the mean relative measurement error is 0.788%,and the mean processing time is 13.65 ms on embedded devices.
基金the financial support of the National Natural Science Foundation of China(12102077,12161076)the Natural Science and Technology Program of Liaoning Province(2023-BS-061).
文摘Recovery is a crucial supporting process for carrier aircraft,where a reasonable landing scheduling is expected to guide the fleet landing safely and quickly.Currently,there is little research on this topic,and most of it neglects potential influence factors,leaving the corresponding supporting efficiency questionable.In this paper,we study the landing scheduling problem for carrier aircraft considering the effects of bolting and aerial refueling.Based on the analysis of recovery mode involving the above factors,two types of primary constraints(i.e.,fuel constraint and wake interval constraint)are first described.Then,taking the landing sequencing as decision variables,a combinatorial optimization model with a compound objective function is formulated.Aiming at an efficient solution,an improved firefly algorithm is designed by integrating multiple evolutionary operators.In addition,a dynamic replanning mechanism is introduced to deal with special situations(i.e.,the occurrence of bolting and fuel shortage),where the high efficiency of the designed algorithm facilitates the online scheduling adjustment within seconds.Finally,numerical simulations with sufficient and insufficient fuel cases are both carried out,highlighting the necessity to consider bolting and aerial refueling during the planning procedure.Simulation results reveal that a higher bolting probability,as well as extra aerial refueling operations caused by fuel shortage,will lead to longer recovery complete time.Meanwhile,due to the strong optimum-seeking capability and solution efficiency of the improved algorithm,adaptive scheduling can be generated within milliseconds to deal with special situations,significantly improving the safety and efficiency of the recovery process.An animation is accessible at bilibili.com/video/BV1QprKY2EwD.
基金supported in part by the Key Research and Development Program of Shandong Province under Grant 2022KJHZ002.
文摘Driven by the global“dual-carbon”goals,hydrogen fuel cell electric vehicles(FCEVs)are being rapidly promoted as a zero-emission transportation solution.However,their large-scale application is constrained by issues such as inefficient operation,poor information flow between vehicles and stations,and potential safety hazards,which are caused by insufficient intelligence of hydrogen refueling stations.This study aims to address these problems by deeply integrating Cellular Vehicle-to-Everything(C-V2X)technology with hydrogen refueling stations,thereby building a safe,efficient,and low-carbon hydrogen energy application ecosystem to promote the global transition to zero-carbon transportation.Firstly,through literature review and technical analysis,this study expounds on the core technologies and process flows of current hydrogen refueling stations,aswell as the technical architecture and development evolution of C-V2X technology.Then,based on the analysis of relevant literature,it proposes a“vehicle-road-station-cloud”collaborative architecture that integrates C-V2X with hydrogen refueling stations.Combined with 5G communication and big data technologies,it elaborates on the implementation path for achieving real-time data interaction among hydrogen refueling stations,hydrogen-powered vehicles,and road infrastructure.This interconnection mode enables hydrogen refueling stations to obtain real-time information of surrounding vehicles,which plays an important role in building a safe,efficient,and low-carbon hydrogen energy application ecosystem and promoting the global transition to zero-carbon transportation.Finally,the future development prospects and potential of this scheme are put forward.
基金This study was co-supported by the National Natural Science Foundation of China(Nos.62103335,61973015,and 61473012)the Young Talent Fund of Association for Science and Technology in Shaanxi,China(No.20230111).
文摘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.
文摘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.
基金This work was supported by the National Natural Science Foundation of China(Nos.61833013,61473012 and 62103335)Key Research Program of Jiangxi Province in China(No.20192BBEL50005).
文摘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.
基金This work was partially supported by Science and Technology Innovation 2030-Key Project of“New Generation Artificial Intelligence”,China(No.2018AAA0102403)the National Natural Science Foundation of China(Nos.U1913602,T2121003,91948204,62103040,and U20B2071)the Open Fund/Postdoctoral Fund of the Laboratory of Cognition and Decision Intelligence for Complex Systems,Institute of Automation,Chinese Academy of Sciences(No.CASIA-KFKT-08).
文摘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.
基金Supported by National Natural Science Foundation of China(Grant Nos.U21B6002 and 52025054)。
文摘Autonomous aerial refueling technology is gaining increasing attention to enhance aircraft combat capabilities.Current research on autonomous refueling focuses mainly on flight control laws,with little attention to the automation of refueling pipes.This leads to high demands on control law performance and navigation accuracy,making it difficult to ensure reliability.To address this,we propose a robotic arm system capable of automatic docking during the flexible aerial refueling process.The system uses a conical kinematic space configuration,offering enhanced stability and impact resistance.The frame-type structure achieves a lightweight design.Additionally,we establish a single-objective optimization model for the connecting rod dimensions and apply a genetic algorithm(GA)for their optimization.We also propose a trajectory-fitting calibration theory based on the robotic arm's special configuration and complete its movement accuracy calibration using a laser tracker.This calibration method reduces the robotic arm's motion error by 71%,achieving an absolute positioning accuracy better than 3.5 mm,which meets the requirements for autonomous aerial refueling.In summary,this research presents a hybrid robotic arm that meets automatic docking requirements,offering a new approach to autonomous aerial refueling.
基金supported by the National Natural Science Foundation of China(No.61304120)
文摘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.
基金supported by the National Natural Science Foundation of China (No. 71101078)the National High Technology Research and Development Program of China (No. 2013AA065303D)the National Environmental Protection Public Welfare Research Fund (No. 201209003 and No.201409021)
文摘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.
基金supported by the National Natural Science Foundation of China(Nos.61473307,61304120)
文摘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.
基金National Natural Science Foundation of China （51075207） Startup Foundation for Introduced Talents of Nanjing University of Aeronautics and Astronautics （1007-YAH10047）
文摘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.
基金supported by the National Natural Science Foundation of China(Nos.61473012 and 51375462)
文摘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.
基金supported by the National Natural Science Foundation of China(No.61473012)。
文摘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.
基金co-supported by the National Basic Research Program of China (Nos. 2012CB316301, 2013CB329403)the National Natural Science Foundation of China (Nos. 61473307, 61304120, 61273023, 61332007)
文摘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.
基金supported by the National Natural Science Foundation of China(Nos.6147330761304120)
文摘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.
基金partially supported by the National Natural Science Foundation of China(No.61333004)partially by the Aeronautical Science Foundation of China(No.20115868009)partially by the open funding project of the State Key Laboratory of Virtual Reality Technology and Systems at Beihang University of China(No.BUAA-VR-13KF-01)
文摘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.
基金supported in part by the National Natural Science Foundation of China(No.61533008)the Fundamental Research Funds for the Central Universities(No. NZ2016104)the Funding of Jiangsu Innovation Program for Graduate Education(No.KYLX15_0276)
文摘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.
基金supported by the National Natural Science Foundation of China(No.61273050)the Aeronautical Science Foundation of China(No.20121352026)
文摘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.
基金Project (No. D000023-16001) supported by the Malaysian Ministry of Higher Education (MOHE) High Impact Research Foundation
文摘Hydrogen is starting to be mentioned as an alternative fuel to replace the fossil fuel in future transportation applications due to its characteristics of zero greenhouse gas emission and high energy efficiency. Before hydrogen fuel and its facilities can be introduced to the public, relevant safety issues and its hazards must be assessed in order to avoid any chance of injury or loss. While a traditional risk assessment has difficulty in prioritizing the risk of failure modes, this paper proposes a new fuzzy-based risk evaluation technique which uses fuzzy value to prioritize the risk of various scenarios. In this study, the final risk of each failure modes was prioritized by using the MATLAB fuzzy logic tool box with a combination of two assessments. The first assessment was concerned with the criteria which affected the actual probability of occurrence. This assessment considered the availability of the standard that was applied to prevent the likelihood of the scenario occurring. On the other hand, the second assessment was focused on evaluating the consequence of the failure by taking into account the availability of detection and the complexity of the failure rather than only the severity of the scenarios. A total of 87 failure scenarios were identified using failure modes and effect analysis (FMEA) procedures on hydrogen refueling station models. Fuzzy-based assessments were performed through risk prioritizing various failure scenarios with a fuzzy value (0 to 1) and risk level (low, medium, and high) while a traditional risk assessment approach presented the risks only in forms of level (low, medium, and/or high). Availability of the fuzzy value enabled further prioritizing on the risk results that fell in the same level of risk. This study concluded that fuzzy-based risk evaluation is able to further prioritize the decisions when compared with a traditional risk assessment method.
