Multi-axle heavy-duty vehicles(MHVs)are essential for military equipment transport due to their safety and stability.However,braking dynamic responses between MHVs and pavement systems still remain underexplored,parti...Multi-axle heavy-duty vehicles(MHVs)are essential for military equipment transport due to their safety and stability.However,braking dynamic responses between MHVs and pavement systems still remain underexplored,particularly regarding their complex load transfer mechanisms.This paper develops an enhanced model of a multi-axle heavy-duty vehicle(MHV)coupled with the uneven and flexible pavement.An advanced coupling iterative method is proposed to solve the highly dimensional equations of the MHV-pavement coupled system.The proposed method was validated through experimental tests,with characteristic parameters of vertical accelerations showing relative errors between 0.42%and 11.80%.The coupling effect and influence mechanism of the braking process are investigated by characteristic parameters of the dynamic responses.Additionally,the influences of braking conditions and pavement parameters are analyzed in time and frequency domains in order to reveal the vibration mechanisms of the coupled system.Moreover,this study establishes a theoretical foundation for monitoring pavement health via vehicle-mounted acceleration signals,which is necessary in military transportation.展开更多
This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hype...This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hypersonic vehicles.In order to increase the control amount,this online control legislation makes use of model predictive control(MPC)that is based on the concept of iterative learning control(ILC).By using offline data to decrease the linearized model’s faults,the strategy may effectively increase the robustness of the control system and guarantee that disturbances can be suppressed.An adaptive fault observer is created based on the suggested ILMPC approach in order to enhance overall fault tolerance by estimating and compensating for actuator disturbance and fault degree.During the derivation process,a linearized model of longitudinal dynamics is established.The suggested ILMPC approach is likely to be used in the design of hypersonic vehicle control systems since numerical simulations have demonstrated that it can decrease tracking error and speed up convergence when compared to the offline controller.展开更多
The cross-domain capabilities of aerial-aquatic vehicles(AAVs)hold significant potential for future airsea integrated combat operations.However,the failure rate of AAVs is higher than that of unmanned systems operatin...The cross-domain capabilities of aerial-aquatic vehicles(AAVs)hold significant potential for future airsea integrated combat operations.However,the failure rate of AAVs is higher than that of unmanned systems operating in a single medium.To ensure the reliable and stable completion of tasks by AAVs,this paper proposes a tiltable quadcopter AAV to mitigate the potential issue of rotor failure,which can lead to high-speed spinning or damage during cross-media transitions.Experimental validation demonstrates that this tiltable quadcopter AAV can transform into a dual-rotor or triple-rotor configuration after losing one or two rotors,allowing it to perform cross-domain movements with enhanced stability and maintain task completion.This enhancement significantly improves its fault tolerance and task reliability.展开更多
This paper presents an investigation on the target-guided coordinated control(TACC)of unmanned surface vehicles(USVs).In the scenario of tracking non-cooperative targets,the status information of the target can only b...This paper presents an investigation on the target-guided coordinated control(TACC)of unmanned surface vehicles(USVs).In the scenario of tracking non-cooperative targets,the status information of the target can only be obtained by some USVs.In order to achieve semi-encirclement tracking of noncooperative targets under maritime security conditions,a fixed-time tracking control method based on dynamic surface control(DSC)is proposed in this paper.Firstly,a novel TACC architecture with decoupled kinematic control law and decoupled kinetic control law was designed to reduce the complexity of control system design.Secondly,the proposed DSC-based target-guided kinematic control law including tracking points pre-allocation strategy and sigmoid artificial potential functions(SigAPFs)can avoid collisions during tracking process and optimize kinematic control output.Finally,a fixed-time TACC system was proposed to achieve fast convergence of kinematic and kinetics errors.The effectiveness of the proposed TACC approach in improving target tracking safety and reducing control output chattering was verified by simulation comparison results.展开更多
The finite volume method was applied to numerically simulate the bottom pressure field induced by regular waves,vehicles in calm water and vehicles in regular waves.The solution of Navier-Stokes(N-S)equations in the v...The finite volume method was applied to numerically simulate the bottom pressure field induced by regular waves,vehicles in calm water and vehicles in regular waves.The solution of Navier-Stokes(N-S)equations in the vicinity of numerical wave tank's boundary was forced towards the wave theoretical solution by incorporating momentum source terms,thereby reducing adverse effects such as wave reflection.Simulations utilizing laminar flow,turbulent flow,and ideal fluid models were all found capable of effectively capturing the waveform and bottom pressure of regular waves,agreeing well with experimental data.In predicting the bottom pressure field of the submerged vehicle,turbulent simulations considering fluid viscosity and boundary layer development provided more accurate predictions for the stern region than inviscid simulations.Due to sphere's diffractive effect,the sphere's bottom pressure field in waves is not a linear superposition of the wave's and the sphere's bottom pressure field.However,a slender submerged vehicle exhibits a weaker diffractive effect on waves,thus the submerged vehicle's bottom pressure field in waves can be approximated as a linear superposition of the wave's and the submerged vehicle's bottom pressure field,which simplifies computation and analysis.展开更多
Trans-medium flight vehicles can combine high aerial maneuverability and underwater concealment ability,which have attracted much attention recently.As the most crucial procedure,the trajectory design generally determ...Trans-medium flight vehicles can combine high aerial maneuverability and underwater concealment ability,which have attracted much attention recently.As the most crucial procedure,the trajectory design generally determines the trans-medium flight vehicle performance.To quantitatively analyze the flight vehicle performance,an entire aerial-aquatic trajectory model is developed in this paper.Different from modeling a trajectory purely for the water entry process,the constructed entire trajectory model has integrated aerial,water entry,and underwater trajectories together,which can consider the influence of the connected trajectories.As for the aerial and underwater trajectories,explicit dynamic models are established to obtain the trajectory parameters.Due to the complicated fluid force during high-velocity water entry,a computational fluid dynamics model is investigated to analyze this phase.The compu-tational domain size is adaptively refined according to the final aerial trajectory state,where the redundant computational domain is removed.An entire trajectory optimization problem is then formulated to maximize the total flight range via tuning the joint states of different trajectories.Simultaneously,several constraints,i.e.,the max impact load,trajectory height,etc.,are involved in the optimization problem.Rather than directly optimizing by a heuristic algorithm,a multi-surrogate cooperative sampling-based optimization method is proposed to alleviate the computational complexity of the entire trajectory optimization problem.In this method,various surrogates coopera-tively generate infill sample points,thereby preventing the poor approximation.After optimization,the total flight range can be improved by 20%,while all the constraints are satisfied.The result demonstrates the effectiveness and practicability of the developed model and optimization framework.展开更多
Unmanned aerial vehicles(UAVs)have become crucial tools in moving target tracking due to their agility and ability to operate in complex,dynamic environments.UAVs must meet several requirements to achieve stable track...Unmanned aerial vehicles(UAVs)have become crucial tools in moving target tracking due to their agility and ability to operate in complex,dynamic environments.UAVs must meet several requirements to achieve stable tracking,including maintaining continuous target visibility amidst occlusions,ensuring flight safety,and achieving smooth trajectory planning.This paper reviews the latest advancements in UAV-based target tracking,highlighting information prediction,tracking strategies,and swarm cooperation.To address challenges including target visibility and occlusion,real-time prediction and tracking in dynamic environments,flight safety and coordination,resource management and energy efficiency,the paper identifies future research directions aimed at improving the performance,reliability,and scalability of UAV tracking system.展开更多
The rapid evolution of unmanned aerial vehicle(UAV)technology and autonomous capabilities has positioned UAV as promising last-mile delivery means.Vehicle and onboard UAV collaborative delivery is introduced as a nove...The rapid evolution of unmanned aerial vehicle(UAV)technology and autonomous capabilities has positioned UAV as promising last-mile delivery means.Vehicle and onboard UAV collaborative delivery is introduced as a novel delivery mode.Spatiotemporal collaboration,along with energy consumption with payload and wind conditions play important roles in delivery route planning.This paper introduces the traveling salesman problem with time window and onboard UAV(TSPTWOUAV)and emphasizes the consideration of real-world scenarios,focusing on time collaboration and energy consumption with wind and payload.To address this,a mixed integer linear programming(MILP)model is formulated to minimize the energy consumption costs of vehicle and UAV.Furthermore,an adaptive large neighborhood search(ALNS)algorithm is applied to identify high-quality solutions efficiently.The effectiveness of the proposed model and algorithm is validated through numerical tests on real geographic instances and sensitivity analysis of key parameters is conducted.展开更多
The exploration of unmanned aerial vehicle(UAV)swarm systems represents a focal point in the research of multiagent systems,with the investigation of their fission-fusion behavior holding significant theoretical and p...The exploration of unmanned aerial vehicle(UAV)swarm systems represents a focal point in the research of multiagent systems,with the investigation of their fission-fusion behavior holding significant theoretical and practical value.This review systematically examines the methods for fission-fusion of UAV swarms from the perspective of multi-agent systems,encompassing the composition of UAV swarm systems and fission-fusion conditions,information interaction mechanisms,and existing fission-fusion approaches.Firstly,considering the constituent units of UAV swarms and the conditions influencing fission-fusion,this paper categorizes and introduces the UAV swarm systems.It further examines the effects and limitations of fission-fusion methods across various categories and conditions.Secondly,a comprehensive analysis of the prevalent information interaction mechanisms within UAV swarms is conducted from the perspective of information interaction structures.The advantages and limitations of various mechanisms in the context of fission-fusion behaviors are summarized and synthesized.Thirdly,this paper consolidates the existing implementation research findings related to the fission-fusion behavior of UAV swarms,identifies unresolved issues in fission-fusion research,and discusses potential solutions.Finally,the paper concludes with a comprehensive summary and systematically outlines future research opportunities.展开更多
This study presents a fragility curve to assess explosively induced damage to military vehicle tires based on shock tube experiments.To replicate lateral damage scenarios that may occur in real battlefield environment...This study presents a fragility curve to assess explosively induced damage to military vehicle tires based on shock tube experiments.To replicate lateral damage scenarios that may occur in real battlefield environments involving missile or bomb detonations,extreme overpressure conditions were generated using a shock tube.The influence of explosive charge mass on tire damage was quantitatively evaluated.Experimental results identified two critical failure thresholds:for loss of pressure,the threshold was 354 kPa peak overpressure and 3052 kPa·ms impulse;for rupture,the values were 485 kPa and 4237 kPa-ms,respectively.The same damage profile was reproduced through finite element analysis(FEA),verifying the reliability of the simulation.A Single Degree of Freedom(SDOF)model and Kingery-Bulmash(K-B)chart were employed to generate pressure-impulse data as a function of standoff distance.These data were applied to a finite element tire model using the BLAST ENHANCED keyword in LS-DYNA.The applied peak overpressures were identical to the experimental values with a 24%-27%difference in impulse.The simulation also captured recurring bead rim separation phenomenon,leading to internal pressure loss consistent with high-speed camera observations from the experiments.The resulting fragility curve clearly defines the threshold conditions for tire damage and provides a standardized damage assessment model applicable to various explosive charge masses and stand-off distances.The proposed model offers a quantitative basis for evaluating tire vulnerability,providing foundational reference data for defense applications.Specifically,the findings are expected to serve as a reliable source for weapon effects analysis and target vulnerability assessments involving wheeled military vehicles.展开更多
For the longitudinal midcourse guidance problem of a cruise-glide integrated hypersonic vehicle(CGHV),an analytical method based on optimal control theory is proposed.This method constructs a guidance dynamics model f...For the longitudinal midcourse guidance problem of a cruise-glide integrated hypersonic vehicle(CGHV),an analytical method based on optimal control theory is proposed.This method constructs a guidance dynamics model for such vehicles,using aerodynamic load as the control variable,and introduces a framework for solving the guidance laws.This framework unifies the design process of guidance laws for both the glide and cruise phases.By decomposing the longitudinal guidance task into position control and velocity control,and minimizing energy consumption as the objective function,the method provides an analytical solution for velocity control load through the calculation of costate variables.This approach requires only the current state and terminal state parameters to determine the guidance law solution.Furthermore,by transforming path constraints into aerodynamic load constraints and solving backwards to obtain the angle of attack,bank angle,and throttle setting,this method ensures a smooth transition from the glide phase to the cruise phase,guaranteeing the successful completion of the guidance task.Finally,the effectiveness and practicality of the proposed method are validated through case simulations and analysis.展开更多
The precise characterization of hypersonic glide vehicle(HGV) maneuver laws in complex flight scenarios still faces challenges. Non-stationary changes in flight state due to abrupt changes in maneuver modes place high...The precise characterization of hypersonic glide vehicle(HGV) maneuver laws in complex flight scenarios still faces challenges. Non-stationary changes in flight state due to abrupt changes in maneuver modes place high demands on the accuracy of modeling methods. To address this issue, a novel maneuver laws modeling and analysis method based on higher order multi-resolution dynamic mode decomposition(HMDMD) is proposed in this work. A joint time-space-frequency decomposition of the vehicle's state sequence in the complex flight scenario is achieved with the higher order Koopman assumption and standard multi-resolution dynamic mode decomposition, and an approximate dynamic model is established. The maneuver laws can be reconstructed and analyzed with extracted multi-scale spatiotemporal modes with clear physical meaning. Based on the dynamic model of HGV, two flight scenarios are established with constant angle of attack and complex maneuver laws, respectively. Simulation results demonstrate that the maneuver laws obtained using the HMDMD method are highly consistent with those derived from the real dynamic model, the modeling accuracy is better than other common modeling methods, and the method has strong interpretability.展开更多
The process of ground vehicle dynamic gravimetry is inevitably affected by the carrier’s maneuvering acceleration,which makes the result contain a large amount of dynamic error.In this paper,we propose a dynamic erro...The process of ground vehicle dynamic gravimetry is inevitably affected by the carrier’s maneuvering acceleration,which makes the result contain a large amount of dynamic error.In this paper,we propose a dynamic error suppression method of gravimetry based on the high-precision acquisition of external velocity for compensating the horizontal error of the inertial plat-form.On the basis of platform gravity measurement,firstly,the dynamic performance of the system is enhanced by optimizing the horizontal damping network of the inertial platform and selecting its parameter.Secondly,an improved federal Kalman filtering algorithm and a fault diagnosis method are designed using strapdown inertial navigation system(SINS),odometer(OD),and laser Doppler velocimeter(LDV).Simulation validates that these methods can improve the accuracy and robustness of the external velocity acquisition.Three survey lines are selected in Tianjin,China,for the gravimetry experiments with different maneuvering levels,and the results demonstrate that after dynamic error suppression,the internal coincidence accuracies of smooth and uniform operation,obvious acceleration and deceleration operation,and high-dynamic operation are improved by 70.2%,73.6%,and 77.9%to reach 0.81 mGal,1.30 mGal,and 1.94 mGal,respectively,and the external coinci-dence accuracies during smooth and uniform operation are improved by 48.6%up to 1.66 mGal.It is shown that the pro-posed method can effectively suppress the dynamic error,and that the accuracy improvement increases with carrier maneuver-ability.However,the amount of residual error that can not be entirely eliminated increases as well,so the ground vehicle dynamic gravimetry should be maintained in the carrier for smooth and uniform operation.展开更多
The maneuverability and stealth of aerial-aquatic vehicles(AAVs)is of significant importance for future integrated air-sea combat missions.To improve the maneuverability and stealth of AAVs near the water surface,this...The maneuverability and stealth of aerial-aquatic vehicles(AAVs)is of significant importance for future integrated air-sea combat missions.To improve the maneuverability and stealth of AAVs near the water surface,this paper proposed a high-maneuverability skipping motion strategy for the tandem twin-rotor AAV,inspired by the motion behavior of the flying fish to avoid aquatic and aerial predators near the water surface.The novel tandem twin-rotor AAV was employed as the research subject and a strategybased ADRC control method for validation,comparing it with a strategy-based PID control method.The results indicate that both control methods enable the designed AAV to achieve high stealth and maneuverability near the water surface with robust control stability.The strategy-based ADRC control method exhibits a certain advantage in controlling height,pitch angle,and reducing impact force.This motion strategy will offer an inspiring approach for the practical application of AAVs to some extent.展开更多
This paper concentrates on addressing the hypersonic glide vehicle(HGV)tracking problem considering the high maneuverability and non-stationary heavy-tailed measurement noise without prior statistics in complicated fl...This paper concentrates on addressing the hypersonic glide vehicle(HGV)tracking problem considering the high maneuverability and non-stationary heavy-tailed measurement noise without prior statistics in complicated flight environments.Since the interacting multiple model(IMM)filtering is famous with its ability to cover the movement property of motion models,the problem is formulated as modeling the non-stationary heavy-tailed measurement noise without any prior statistics in the IMM framework.Firstly,without any prior statistics,the Gaussian-inverse Wishart distribution is embedded in the improved Pearson type-VII(PTV)distribution,which can adaptively adjust the parameters to model the non-stationary heavytailed measurement noise.Besides,degree of freedom(DOF)parameters are surrogated by the maximization of evidence lower bound(ELBO)in the variational Bayesian optimization framework instead of fixed value to handle uncertain non-Gaussian degrees.Then,this paper analytically derives fusion forms based on the maximum Versoria fusion criterion instead of the moment matching approach,which can provide a precise approximation for the PTV mixture distribution in the mixing and output steps combined with the weight Kullback-Leibler average theory.Simulation results demonstrate the superiority and robustness of the proposed algorithm in typical HGVs tracking when the measurement noise without priori statistics is non-stationary.展开更多
Hypersonic Glide Vehicles(HGVs)are advanced aircraft that can achieve extremely high speeds(generally over 5 Mach)and maneuverability within the Earth's atmosphere.HGV trajectory prediction is crucial for effectiv...Hypersonic Glide Vehicles(HGVs)are advanced aircraft that can achieve extremely high speeds(generally over 5 Mach)and maneuverability within the Earth's atmosphere.HGV trajectory prediction is crucial for effective defense planning and interception strategies.In recent years,HGV trajectory prediction methods based on deep learning have the great potential to significantly enhance prediction accuracy and efficiency.However,it's still challenging to strike a balance between improving prediction performance and reducing computation costs of the deep learning trajectory prediction models.To solve this problem,we propose a new deep learning framework(FECA-LSMN)for efficient HGV trajectory prediction.The model first uses a Frequency Enhanced Channel Attention(FECA)module to facilitate the fusion of different HGV trajectory features,and then subsequently employs a Light Sampling-oriented Multi-Layer Perceptron Network(LSMN)based on simple MLP-based structures to extract long/shortterm HGV trajectory features for accurate trajectory prediction.Also,we employ a new data normalization method called reversible instance normalization(RevIN)to enhance the prediction accuracy and training stability of the network.Compared to other popular trajectory prediction models based on LSTM,GRU and Transformer,our FECA-LSMN model achieves leading or comparable performance in terms of RMSE,MAE and MAPE metrics while demonstrating notably faster computation time.The ablation experiments show that the incorporation of the FECA module significantly improves the prediction performance of the network.The RevIN data normalization technique outperforms traditional min-max normalization as well.展开更多
A security issue with multi-sensor unmanned aerial vehicle(UAV)cyber physical systems(CPS)from the viewpoint of a false data injection(FDI)attacker is investigated in this paper.The FDI attacker can employ attacks on ...A security issue with multi-sensor unmanned aerial vehicle(UAV)cyber physical systems(CPS)from the viewpoint of a false data injection(FDI)attacker is investigated in this paper.The FDI attacker can employ attacks on feedback and feed-forward channels simultaneously with limited resource.The attacker aims at degrading the UAV CPS's estimation performance to the max while keeping stealthiness characterized by the Kullback-Leibler(K-L)divergence.The attacker is resource limited which can only attack part of sensors,and the attacked sensor as well as specific forms of attack signals at each instant should be considered by the attacker.Also,the sensor selection principle is investigated with respect to time invariant attack covariances.Additionally,the optimal switching attack strategies in regard to time variant attack covariances are modeled as a multi-agent Markov decision process(MDP)with hybrid discrete-continuous action space.Then,the multi-agent MDP is solved by utilizing the deep Multi-agent parameterized Q-networks(MAPQN)method.Ultimately,a quadrotor near hover system is used to validate the effectiveness of the results in the simulation section.展开更多
The high cost and low efficiency of full-scale vehicle experiments and numerical simulations limit the efficient development of armored vehicle occupant protection systems.The floor-occupant-seat local simulation mode...The high cost and low efficiency of full-scale vehicle experiments and numerical simulations limit the efficient development of armored vehicle occupant protection systems.The floor-occupant-seat local simulation model provides an alternative solution for quickly evaluating the performance of occupant protection systems.However,the error and rationality of the loading of the thin-walled floor in the local model cannot be ignored.This study proposed an equivalent loading method for the local model,which includes two parts:the dimensionality reduction method for acceleration matrix and the joint optimization framework for equivalent node coordinates.In the dimensionality reduction method,the dimension of the acceleration matrix was reduced based on the improved kernel principal component analysis(KPCA),and a dynamic variable bandwidth was introduced to address the limitation of failing to effectively measure the similarity between acceleration data in conventional KPCA.In addition,a least squares problem with forced displacement constraints was constructed to solve the correction matrix,thereby achieving the scale restoration process of the principal component acceleration matrix.The joint optimization framework for coordinates consists of the error assessment of response time histories(EARTH)and Bayesian optimization.In this framework,the local loading error of the equivalent acceleration matrix is taken as the Bayesian optimization objective,which is quantified and scored by EARTH.The expected improvement acquisition function was used to select the new set of the equivalent acceleration node coordinates for the self-updating optimization of the observation dataset and Gaussian process surrogate model.We reduced the dimension of the acceleration matrix from 2256 to 7,while retaining 91%of the information features.The comprehensive error score of occupant's lower limb response in the local model increased from 58.5%to 80.4%.The proposed equivalent loading method provides a solution for the rapid and reliable development of occupant protection systems.展开更多
As commercial drone delivery becomes increasingly popular,the extension of the vehicle routing problem with drones(VRPD)is emerging as an optimization problem of inter-ests.This paper studies a variant of VRPD in mult...As commercial drone delivery becomes increasingly popular,the extension of the vehicle routing problem with drones(VRPD)is emerging as an optimization problem of inter-ests.This paper studies a variant of VRPD in multi-trip and multi-drop(VRP-mmD).The problem aims at making schedules for the trucks and drones such that the total travel time is minimized.This paper formulate the problem with a mixed integer program-ming model and propose a two-phase algorithm,i.e.,a parallel route construction heuristic(PRCH)for the first phase and an adaptive neighbor searching heuristic(ANSH)for the second phase.The PRCH generates an initial solution by con-currently assigning as many nodes as possible to the truck–drone pair to progressively reduce the waiting time at the rendezvous node in the first phase.Then the ANSH improves the initial solution by adaptively exploring the neighborhoods in the second phase.Numerical tests on some benchmark data are conducted to verify the performance of the algorithm.The results show that the proposed algorithm can found better solu-tions than some state-of-the-art methods for all instances.More-over,an extensive analysis highlights the stability of the pro-posed algorithm.展开更多
As a crucial process in the coordinated strikes of unmanned aerial vehicles(UAVs), weapon-target assignment is vital for optimizing the allocation of available weapons and effectively exploiting the capabilities of UA...As a crucial process in the coordinated strikes of unmanned aerial vehicles(UAVs), weapon-target assignment is vital for optimizing the allocation of available weapons and effectively exploiting the capabilities of UAVs. Existing weapon-target assignment methods primarily focus on macro cluster constraints while neglecting individual strategy updates. This paper proposes a novel weapon-target assignment method for UAVs based on the multi-strategy threshold public goods game(PGG). By analyzing the concept mapping between weapon-target assignment for UAVs and multi-strategy threshold PGG, a weapon-target assignment model for UAVs based on the multi-strategy threshold PGG is established, which is adaptively complemented by the diverse cooperation-defection strategy library and the utility function based on the threshold mechanism. Additionally, a multi-chain Markov is formulated to quantitatively describe the stochastic evolutionary dynamics, whose evolutionary stable distribution is theoretically derived through the development of a strategy update rule based on preference-based aspiration dynamic. Numerical simulation results validate the feasibility and effectiveness of the proposed method, and the impacts of selection intensity, preference degree and threshold on the evolutionary stable distribution are analyzed. Comparative simulations show that the proposed method outperforms GWO, DE, and NSGA-II, achieving 17.18% higher expected utility than NSGA-II and reducing evolutionary stable times by 25% in large-scale scenario.展开更多
基金National Defense Basic Scientific Research Program of China(Grant No.JCKY2021602B030).
文摘Multi-axle heavy-duty vehicles(MHVs)are essential for military equipment transport due to their safety and stability.However,braking dynamic responses between MHVs and pavement systems still remain underexplored,particularly regarding their complex load transfer mechanisms.This paper develops an enhanced model of a multi-axle heavy-duty vehicle(MHV)coupled with the uneven and flexible pavement.An advanced coupling iterative method is proposed to solve the highly dimensional equations of the MHV-pavement coupled system.The proposed method was validated through experimental tests,with characteristic parameters of vertical accelerations showing relative errors between 0.42%and 11.80%.The coupling effect and influence mechanism of the braking process are investigated by characteristic parameters of the dynamic responses.Additionally,the influences of braking conditions and pavement parameters are analyzed in time and frequency domains in order to reveal the vibration mechanisms of the coupled system.Moreover,this study establishes a theoretical foundation for monitoring pavement health via vehicle-mounted acceleration signals,which is necessary in military transportation.
基金supported by the National Natural Science Foundation of China(12072090).
文摘This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hypersonic vehicles.In order to increase the control amount,this online control legislation makes use of model predictive control(MPC)that is based on the concept of iterative learning control(ILC).By using offline data to decrease the linearized model’s faults,the strategy may effectively increase the robustness of the control system and guarantee that disturbances can be suppressed.An adaptive fault observer is created based on the suggested ILMPC approach in order to enhance overall fault tolerance by estimating and compensating for actuator disturbance and fault degree.During the derivation process,a linearized model of longitudinal dynamics is established.The suggested ILMPC approach is likely to be used in the design of hypersonic vehicle control systems since numerical simulations have demonstrated that it can decrease tracking error and speed up convergence when compared to the offline controller.
基金supported by Southern Marine Science and Engineering Guangdong Laboratory Grant No.SML2023SP229。
文摘The cross-domain capabilities of aerial-aquatic vehicles(AAVs)hold significant potential for future airsea integrated combat operations.However,the failure rate of AAVs is higher than that of unmanned systems operating in a single medium.To ensure the reliable and stable completion of tasks by AAVs,this paper proposes a tiltable quadcopter AAV to mitigate the potential issue of rotor failure,which can lead to high-speed spinning or damage during cross-media transitions.Experimental validation demonstrates that this tiltable quadcopter AAV can transform into a dual-rotor or triple-rotor configuration after losing one or two rotors,allowing it to perform cross-domain movements with enhanced stability and maintain task completion.This enhancement significantly improves its fault tolerance and task reliability.
文摘This paper presents an investigation on the target-guided coordinated control(TACC)of unmanned surface vehicles(USVs).In the scenario of tracking non-cooperative targets,the status information of the target can only be obtained by some USVs.In order to achieve semi-encirclement tracking of noncooperative targets under maritime security conditions,a fixed-time tracking control method based on dynamic surface control(DSC)is proposed in this paper.Firstly,a novel TACC architecture with decoupled kinematic control law and decoupled kinetic control law was designed to reduce the complexity of control system design.Secondly,the proposed DSC-based target-guided kinematic control law including tracking points pre-allocation strategy and sigmoid artificial potential functions(SigAPFs)can avoid collisions during tracking process and optimize kinematic control output.Finally,a fixed-time TACC system was proposed to achieve fast convergence of kinematic and kinetics errors.The effectiveness of the proposed TACC approach in improving target tracking safety and reducing control output chattering was verified by simulation comparison results.
文摘The finite volume method was applied to numerically simulate the bottom pressure field induced by regular waves,vehicles in calm water and vehicles in regular waves.The solution of Navier-Stokes(N-S)equations in the vicinity of numerical wave tank's boundary was forced towards the wave theoretical solution by incorporating momentum source terms,thereby reducing adverse effects such as wave reflection.Simulations utilizing laminar flow,turbulent flow,and ideal fluid models were all found capable of effectively capturing the waveform and bottom pressure of regular waves,agreeing well with experimental data.In predicting the bottom pressure field of the submerged vehicle,turbulent simulations considering fluid viscosity and boundary layer development provided more accurate predictions for the stern region than inviscid simulations.Due to sphere's diffractive effect,the sphere's bottom pressure field in waves is not a linear superposition of the wave's and the sphere's bottom pressure field.However,a slender submerged vehicle exhibits a weaker diffractive effect on waves,thus the submerged vehicle's bottom pressure field in waves can be approximated as a linear superposition of the wave's and the submerged vehicle's bottom pressure field,which simplifies computation and analysis.
基金supported by the National Natural Science Foundation of China(Grant Nos.52425211,52272360,and 52472394)Chongqing Natural Science Foundation(CSTB2023NSCQ-MSX0300)。
文摘Trans-medium flight vehicles can combine high aerial maneuverability and underwater concealment ability,which have attracted much attention recently.As the most crucial procedure,the trajectory design generally determines the trans-medium flight vehicle performance.To quantitatively analyze the flight vehicle performance,an entire aerial-aquatic trajectory model is developed in this paper.Different from modeling a trajectory purely for the water entry process,the constructed entire trajectory model has integrated aerial,water entry,and underwater trajectories together,which can consider the influence of the connected trajectories.As for the aerial and underwater trajectories,explicit dynamic models are established to obtain the trajectory parameters.Due to the complicated fluid force during high-velocity water entry,a computational fluid dynamics model is investigated to analyze this phase.The compu-tational domain size is adaptively refined according to the final aerial trajectory state,where the redundant computational domain is removed.An entire trajectory optimization problem is then formulated to maximize the total flight range via tuning the joint states of different trajectories.Simultaneously,several constraints,i.e.,the max impact load,trajectory height,etc.,are involved in the optimization problem.Rather than directly optimizing by a heuristic algorithm,a multi-surrogate cooperative sampling-based optimization method is proposed to alleviate the computational complexity of the entire trajectory optimization problem.In this method,various surrogates coopera-tively generate infill sample points,thereby preventing the poor approximation.After optimization,the total flight range can be improved by 20%,while all the constraints are satisfied.The result demonstrates the effectiveness and practicability of the developed model and optimization framework.
基金financial support provided by the Natural Science Foundation of Hunan Province of China(Grant No.2021JJ10045)the Open Research Subject of State Key Laboratory of Intelligent Game(Grant No.ZBKF-24-01)+1 种基金the Postdoctoral Fellowship Program of CPSF(Grant No.GZB20240989)the China Postdoctoral Science Foundation(Grant No.2024M754304)。
文摘Unmanned aerial vehicles(UAVs)have become crucial tools in moving target tracking due to their agility and ability to operate in complex,dynamic environments.UAVs must meet several requirements to achieve stable tracking,including maintaining continuous target visibility amidst occlusions,ensuring flight safety,and achieving smooth trajectory planning.This paper reviews the latest advancements in UAV-based target tracking,highlighting information prediction,tracking strategies,and swarm cooperation.To address challenges including target visibility and occlusion,real-time prediction and tracking in dynamic environments,flight safety and coordination,resource management and energy efficiency,the paper identifies future research directions aimed at improving the performance,reliability,and scalability of UAV tracking system.
基金Fundamental Research Funds for the Central Universities(2024JBZX038)National Natural Science F oundation of China(62076023)。
文摘The rapid evolution of unmanned aerial vehicle(UAV)technology and autonomous capabilities has positioned UAV as promising last-mile delivery means.Vehicle and onboard UAV collaborative delivery is introduced as a novel delivery mode.Spatiotemporal collaboration,along with energy consumption with payload and wind conditions play important roles in delivery route planning.This paper introduces the traveling salesman problem with time window and onboard UAV(TSPTWOUAV)and emphasizes the consideration of real-world scenarios,focusing on time collaboration and energy consumption with wind and payload.To address this,a mixed integer linear programming(MILP)model is formulated to minimize the energy consumption costs of vehicle and UAV.Furthermore,an adaptive large neighborhood search(ALNS)algorithm is applied to identify high-quality solutions efficiently.The effectiveness of the proposed model and algorithm is validated through numerical tests on real geographic instances and sensitivity analysis of key parameters is conducted.
基金supported by the National Natural Science Foundation of China(U20B2042).
文摘The exploration of unmanned aerial vehicle(UAV)swarm systems represents a focal point in the research of multiagent systems,with the investigation of their fission-fusion behavior holding significant theoretical and practical value.This review systematically examines the methods for fission-fusion of UAV swarms from the perspective of multi-agent systems,encompassing the composition of UAV swarm systems and fission-fusion conditions,information interaction mechanisms,and existing fission-fusion approaches.Firstly,considering the constituent units of UAV swarms and the conditions influencing fission-fusion,this paper categorizes and introduces the UAV swarm systems.It further examines the effects and limitations of fission-fusion methods across various categories and conditions.Secondly,a comprehensive analysis of the prevalent information interaction mechanisms within UAV swarms is conducted from the perspective of information interaction structures.The advantages and limitations of various mechanisms in the context of fission-fusion behaviors are summarized and synthesized.Thirdly,this paper consolidates the existing implementation research findings related to the fission-fusion behavior of UAV swarms,identifies unresolved issues in fission-fusion research,and discusses potential solutions.Finally,the paper concludes with a comprehensive summary and systematically outlines future research opportunities.
基金part of the Agency for Defense Development(ADD)research project on Weapon lethality/effectiveness analysis technology for material targets and grant funded by the korean goverment(511225-912A03301)。
文摘This study presents a fragility curve to assess explosively induced damage to military vehicle tires based on shock tube experiments.To replicate lateral damage scenarios that may occur in real battlefield environments involving missile or bomb detonations,extreme overpressure conditions were generated using a shock tube.The influence of explosive charge mass on tire damage was quantitatively evaluated.Experimental results identified two critical failure thresholds:for loss of pressure,the threshold was 354 kPa peak overpressure and 3052 kPa·ms impulse;for rupture,the values were 485 kPa and 4237 kPa-ms,respectively.The same damage profile was reproduced through finite element analysis(FEA),verifying the reliability of the simulation.A Single Degree of Freedom(SDOF)model and Kingery-Bulmash(K-B)chart were employed to generate pressure-impulse data as a function of standoff distance.These data were applied to a finite element tire model using the BLAST ENHANCED keyword in LS-DYNA.The applied peak overpressures were identical to the experimental values with a 24%-27%difference in impulse.The simulation also captured recurring bead rim separation phenomenon,leading to internal pressure loss consistent with high-speed camera observations from the experiments.The resulting fragility curve clearly defines the threshold conditions for tire damage and provides a standardized damage assessment model applicable to various explosive charge masses and stand-off distances.The proposed model offers a quantitative basis for evaluating tire vulnerability,providing foundational reference data for defense applications.Specifically,the findings are expected to serve as a reliable source for weapon effects analysis and target vulnerability assessments involving wheeled military vehicles.
基金supported by the National Natural Science Foundation of China(Grant Nos.62473374,62403487 and U2441243).
文摘For the longitudinal midcourse guidance problem of a cruise-glide integrated hypersonic vehicle(CGHV),an analytical method based on optimal control theory is proposed.This method constructs a guidance dynamics model for such vehicles,using aerodynamic load as the control variable,and introduces a framework for solving the guidance laws.This framework unifies the design process of guidance laws for both the glide and cruise phases.By decomposing the longitudinal guidance task into position control and velocity control,and minimizing energy consumption as the objective function,the method provides an analytical solution for velocity control load through the calculation of costate variables.This approach requires only the current state and terminal state parameters to determine the guidance law solution.Furthermore,by transforming path constraints into aerodynamic load constraints and solving backwards to obtain the angle of attack,bank angle,and throttle setting,this method ensures a smooth transition from the glide phase to the cruise phase,guaranteeing the successful completion of the guidance task.Finally,the effectiveness and practicality of the proposed method are validated through case simulations and analysis.
基金supported by the National Natural Science Foundation of China (Grant No. 12302056)the Postdoctoral Fellowship Program of CPSF:GZC20233445。
文摘The precise characterization of hypersonic glide vehicle(HGV) maneuver laws in complex flight scenarios still faces challenges. Non-stationary changes in flight state due to abrupt changes in maneuver modes place high demands on the accuracy of modeling methods. To address this issue, a novel maneuver laws modeling and analysis method based on higher order multi-resolution dynamic mode decomposition(HMDMD) is proposed in this work. A joint time-space-frequency decomposition of the vehicle's state sequence in the complex flight scenario is achieved with the higher order Koopman assumption and standard multi-resolution dynamic mode decomposition, and an approximate dynamic model is established. The maneuver laws can be reconstructed and analyzed with extracted multi-scale spatiotemporal modes with clear physical meaning. Based on the dynamic model of HGV, two flight scenarios are established with constant angle of attack and complex maneuver laws, respectively. Simulation results demonstrate that the maneuver laws obtained using the HMDMD method are highly consistent with those derived from the real dynamic model, the modeling accuracy is better than other common modeling methods, and the method has strong interpretability.
基金supported by the Shanxi Provincial Natural Science Basic Research Program Young Talent Project(S2019-JC-QN-2408).
文摘The process of ground vehicle dynamic gravimetry is inevitably affected by the carrier’s maneuvering acceleration,which makes the result contain a large amount of dynamic error.In this paper,we propose a dynamic error suppression method of gravimetry based on the high-precision acquisition of external velocity for compensating the horizontal error of the inertial plat-form.On the basis of platform gravity measurement,firstly,the dynamic performance of the system is enhanced by optimizing the horizontal damping network of the inertial platform and selecting its parameter.Secondly,an improved federal Kalman filtering algorithm and a fault diagnosis method are designed using strapdown inertial navigation system(SINS),odometer(OD),and laser Doppler velocimeter(LDV).Simulation validates that these methods can improve the accuracy and robustness of the external velocity acquisition.Three survey lines are selected in Tianjin,China,for the gravimetry experiments with different maneuvering levels,and the results demonstrate that after dynamic error suppression,the internal coincidence accuracies of smooth and uniform operation,obvious acceleration and deceleration operation,and high-dynamic operation are improved by 70.2%,73.6%,and 77.9%to reach 0.81 mGal,1.30 mGal,and 1.94 mGal,respectively,and the external coinci-dence accuracies during smooth and uniform operation are improved by 48.6%up to 1.66 mGal.It is shown that the pro-posed method can effectively suppress the dynamic error,and that the accuracy improvement increases with carrier maneuver-ability.However,the amount of residual error that can not be entirely eliminated increases as well,so the ground vehicle dynamic gravimetry should be maintained in the carrier for smooth and uniform operation.
基金supported by Southern Marine Science and Guangdong Laboratory(Zhuhai)(Grant No.SML2023SP229)。
文摘The maneuverability and stealth of aerial-aquatic vehicles(AAVs)is of significant importance for future integrated air-sea combat missions.To improve the maneuverability and stealth of AAVs near the water surface,this paper proposed a high-maneuverability skipping motion strategy for the tandem twin-rotor AAV,inspired by the motion behavior of the flying fish to avoid aquatic and aerial predators near the water surface.The novel tandem twin-rotor AAV was employed as the research subject and a strategybased ADRC control method for validation,comparing it with a strategy-based PID control method.The results indicate that both control methods enable the designed AAV to achieve high stealth and maneuverability near the water surface with robust control stability.The strategy-based ADRC control method exhibits a certain advantage in controlling height,pitch angle,and reducing impact force.This motion strategy will offer an inspiring approach for the practical application of AAVs to some extent.
基金supported by the National Natural Science Foundation of China(12072090).
文摘This paper concentrates on addressing the hypersonic glide vehicle(HGV)tracking problem considering the high maneuverability and non-stationary heavy-tailed measurement noise without prior statistics in complicated flight environments.Since the interacting multiple model(IMM)filtering is famous with its ability to cover the movement property of motion models,the problem is formulated as modeling the non-stationary heavy-tailed measurement noise without any prior statistics in the IMM framework.Firstly,without any prior statistics,the Gaussian-inverse Wishart distribution is embedded in the improved Pearson type-VII(PTV)distribution,which can adaptively adjust the parameters to model the non-stationary heavytailed measurement noise.Besides,degree of freedom(DOF)parameters are surrogated by the maximization of evidence lower bound(ELBO)in the variational Bayesian optimization framework instead of fixed value to handle uncertain non-Gaussian degrees.Then,this paper analytically derives fusion forms based on the maximum Versoria fusion criterion instead of the moment matching approach,which can provide a precise approximation for the PTV mixture distribution in the mixing and output steps combined with the weight Kullback-Leibler average theory.Simulation results demonstrate the superiority and robustness of the proposed algorithm in typical HGVs tracking when the measurement noise without priori statistics is non-stationary.
文摘Hypersonic Glide Vehicles(HGVs)are advanced aircraft that can achieve extremely high speeds(generally over 5 Mach)and maneuverability within the Earth's atmosphere.HGV trajectory prediction is crucial for effective defense planning and interception strategies.In recent years,HGV trajectory prediction methods based on deep learning have the great potential to significantly enhance prediction accuracy and efficiency.However,it's still challenging to strike a balance between improving prediction performance and reducing computation costs of the deep learning trajectory prediction models.To solve this problem,we propose a new deep learning framework(FECA-LSMN)for efficient HGV trajectory prediction.The model first uses a Frequency Enhanced Channel Attention(FECA)module to facilitate the fusion of different HGV trajectory features,and then subsequently employs a Light Sampling-oriented Multi-Layer Perceptron Network(LSMN)based on simple MLP-based structures to extract long/shortterm HGV trajectory features for accurate trajectory prediction.Also,we employ a new data normalization method called reversible instance normalization(RevIN)to enhance the prediction accuracy and training stability of the network.Compared to other popular trajectory prediction models based on LSTM,GRU and Transformer,our FECA-LSMN model achieves leading or comparable performance in terms of RMSE,MAE and MAPE metrics while demonstrating notably faster computation time.The ablation experiments show that the incorporation of the FECA module significantly improves the prediction performance of the network.The RevIN data normalization technique outperforms traditional min-max normalization as well.
文摘A security issue with multi-sensor unmanned aerial vehicle(UAV)cyber physical systems(CPS)from the viewpoint of a false data injection(FDI)attacker is investigated in this paper.The FDI attacker can employ attacks on feedback and feed-forward channels simultaneously with limited resource.The attacker aims at degrading the UAV CPS's estimation performance to the max while keeping stealthiness characterized by the Kullback-Leibler(K-L)divergence.The attacker is resource limited which can only attack part of sensors,and the attacked sensor as well as specific forms of attack signals at each instant should be considered by the attacker.Also,the sensor selection principle is investigated with respect to time invariant attack covariances.Additionally,the optimal switching attack strategies in regard to time variant attack covariances are modeled as a multi-agent Markov decision process(MDP)with hybrid discrete-continuous action space.Then,the multi-agent MDP is solved by utilizing the deep Multi-agent parameterized Q-networks(MAPQN)method.Ultimately,a quadrotor near hover system is used to validate the effectiveness of the results in the simulation section.
基金supported by the National Natural Science Foundation of China(Grant Nos.52272437 and 52272370)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX24_0635)。
文摘The high cost and low efficiency of full-scale vehicle experiments and numerical simulations limit the efficient development of armored vehicle occupant protection systems.The floor-occupant-seat local simulation model provides an alternative solution for quickly evaluating the performance of occupant protection systems.However,the error and rationality of the loading of the thin-walled floor in the local model cannot be ignored.This study proposed an equivalent loading method for the local model,which includes two parts:the dimensionality reduction method for acceleration matrix and the joint optimization framework for equivalent node coordinates.In the dimensionality reduction method,the dimension of the acceleration matrix was reduced based on the improved kernel principal component analysis(KPCA),and a dynamic variable bandwidth was introduced to address the limitation of failing to effectively measure the similarity between acceleration data in conventional KPCA.In addition,a least squares problem with forced displacement constraints was constructed to solve the correction matrix,thereby achieving the scale restoration process of the principal component acceleration matrix.The joint optimization framework for coordinates consists of the error assessment of response time histories(EARTH)and Bayesian optimization.In this framework,the local loading error of the equivalent acceleration matrix is taken as the Bayesian optimization objective,which is quantified and scored by EARTH.The expected improvement acquisition function was used to select the new set of the equivalent acceleration node coordinates for the self-updating optimization of the observation dataset and Gaussian process surrogate model.We reduced the dimension of the acceleration matrix from 2256 to 7,while retaining 91%of the information features.The comprehensive error score of occupant's lower limb response in the local model increased from 58.5%to 80.4%.The proposed equivalent loading method provides a solution for the rapid and reliable development of occupant protection systems.
文摘As commercial drone delivery becomes increasingly popular,the extension of the vehicle routing problem with drones(VRPD)is emerging as an optimization problem of inter-ests.This paper studies a variant of VRPD in multi-trip and multi-drop(VRP-mmD).The problem aims at making schedules for the trucks and drones such that the total travel time is minimized.This paper formulate the problem with a mixed integer program-ming model and propose a two-phase algorithm,i.e.,a parallel route construction heuristic(PRCH)for the first phase and an adaptive neighbor searching heuristic(ANSH)for the second phase.The PRCH generates an initial solution by con-currently assigning as many nodes as possible to the truck–drone pair to progressively reduce the waiting time at the rendezvous node in the first phase.Then the ANSH improves the initial solution by adaptively exploring the neighborhoods in the second phase.Numerical tests on some benchmark data are conducted to verify the performance of the algorithm.The results show that the proposed algorithm can found better solu-tions than some state-of-the-art methods for all instances.More-over,an extensive analysis highlights the stability of the pro-posed algorithm.
基金supported by the National Natural Science Foundation of China (No. 62073267)。
文摘As a crucial process in the coordinated strikes of unmanned aerial vehicles(UAVs), weapon-target assignment is vital for optimizing the allocation of available weapons and effectively exploiting the capabilities of UAVs. Existing weapon-target assignment methods primarily focus on macro cluster constraints while neglecting individual strategy updates. This paper proposes a novel weapon-target assignment method for UAVs based on the multi-strategy threshold public goods game(PGG). By analyzing the concept mapping between weapon-target assignment for UAVs and multi-strategy threshold PGG, a weapon-target assignment model for UAVs based on the multi-strategy threshold PGG is established, which is adaptively complemented by the diverse cooperation-defection strategy library and the utility function based on the threshold mechanism. Additionally, a multi-chain Markov is formulated to quantitatively describe the stochastic evolutionary dynamics, whose evolutionary stable distribution is theoretically derived through the development of a strategy update rule based on preference-based aspiration dynamic. Numerical simulation results validate the feasibility and effectiveness of the proposed method, and the impacts of selection intensity, preference degree and threshold on the evolutionary stable distribution are analyzed. Comparative simulations show that the proposed method outperforms GWO, DE, and NSGA-II, achieving 17.18% higher expected utility than NSGA-II and reducing evolutionary stable times by 25% in large-scale scenario.
