Unmanned Aerial Vehicle(UAV)swarm collaboration enhances mission effectiveness.However,fixed-wing UAV swarm flights face collaborative safety control problems within a limited airspace in complex environments.Aimed at...Unmanned Aerial Vehicle(UAV)swarm collaboration enhances mission effectiveness.However,fixed-wing UAV swarm flights face collaborative safety control problems within a limited airspace in complex environments.Aimed at the cooperative control problem of fixed-wing UAV swarm flights under the airspace constraints of a virtual tube in a complex environment,this paper proposes a behavior-based distributed control method for fixed-wing UAV swarm considering flight safety constraints.Considering the fixed-wing UAV swarm flight problem in complex environment,a virtual tube model based on generator curve is established.The tube keeping,centerline tracking and flight safety behavioral control strategies of the UAV swarm are designed to ensure that the UAV swarm flies along the inside of the virtual tube safety and does not go beyond its boundary.On this basis,a maneuvering decision-making method based on behavioral fusion is proposed to ensure the safe flight of UAV swarm in the restricted airspace.This cooperative control method eliminates the need for respective pre-planned trajectories,reduces communication requirements,and achieves a high level of intelligence.Simulation results show that the proposed behaviorbased UAV swarm cooperative control method is able to make the fixed-wing UAV swarm,which is faster and unable to hover,fly along the virtual tube airspace under various virtual tube shapes and different swarm sizes,and the spacing between the UAVs is larger than the minimum safe distance during the flight.展开更多
Recently,unmanned aerial vehicle(UAV)-aided free-space optical(FSO)communication has attracted widespread attentions.However,most of the existing research focuses on communication performance only.The authors investig...Recently,unmanned aerial vehicle(UAV)-aided free-space optical(FSO)communication has attracted widespread attentions.However,most of the existing research focuses on communication performance only.The authors investigate the integrated scheduling of communication,sensing,and control for UAV-aided FSO communication systems.Initially,a sensing-control model is established via the control theory.Moreover,an FSO communication channel model is established by considering the effects of atmospheric loss,atmospheric turbulence,geometrical loss,and angle-of-arrival fluctuation.Then,the relationship between the motion control of the UAV and radial displacement is obtained to link the control aspect and communication aspect.Assuming that the base station has instantaneous channel state information(CSI)or statistical CSI,the thresholds of the sensing-control pattern activation are designed,respectively.Finally,an integrated scheduling scheme for performing communication,sensing,and control is proposed.Numerical results indicate that,compared with conventional time-triggered scheme,the proposed integrated scheduling scheme obtains comparable communication and control performance,but reduces the sensing consumed power by 52.46%.展开更多
This paper proposes a distributed event-triggered control(ETC)framework to address cooperative target fencing challenges in UAV swarm.The proposed architecture eliminates the reliance on preset formation parameters wh...This paper proposes a distributed event-triggered control(ETC)framework to address cooperative target fencing challenges in UAV swarm.The proposed architecture eliminates the reliance on preset formation parameters while achieving multi-objective cooperative control for target fencing,network connectivity preservation,collision avoidance,and communication efficiency optimization.Firstly,a differential state observer is constructed to obtain the target's unmeasurable states.Secondly,leveraging swarm selforganization principles,a geometric-constraint-free distributed fencing controller is designed by integrating potential field methods with consensus theory.The controller dynamically adjusts inter-UAV distances via single potential function,enabling coordinated optimization of persistent network connectivity and collision-free motion during target fencing.Thirdly,a dual-threshold ETC mechanism based on velocity consensus deviation and fencing error is proposed,which can be triggered based on task features to dynamically adjust the communication frequency,significantly reduce the communication burden and exclude Zeno behavior.Theoretical analysis demonstrates the stability of closed-loop systems.Multi-scenario simulations show that the proposed method can achieve robust fencing under target maneuverability,partial UAV failures,and communication disturbances.展开更多
The maneuvering of a large-scale unmanned aerial vehicle(UAV)swarm,notable for flexible flight with collisionfree,is still challenging due to the significant number of UAVs and the compact configuration of the swarm.I...The maneuvering of a large-scale unmanned aerial vehicle(UAV)swarm,notable for flexible flight with collisionfree,is still challenging due to the significant number of UAVs and the compact configuration of the swarm.In light of this problem,a novel parallel control method that utilizes space and time transformation is proposed.First,the swarm is decomposed based on a grouping-hierarchical strategy,while the distinct flight roles are assigned to each UAV.Then,to achieve the desired configuration(DCF)in the real world,a bijection transformation is conducted in the space domain,converting an arbitrarily general configuration(GCF)into a standard configuration(SCF)in the virtual space.Further,to improve the flexibility of the swarm,the time scaling transformation is adopted in the time domain,which ensures the desired prescribed-time convergence of the swarm independent of initial conditions.Finally,simulation results demonstrate that collision-free maneuvering,including formation changes and turning,can be effectively and rapidly achieved by the proposed parallel control method.Overall,this research contributes a viable solution for enhancing cooperation among largescale UAV swarms.展开更多
This article investigates the approaching control for fixed-wing Unmanned Aerial Vehi-cle(UAV)aerial recovery in the presence of pre-specified performance requirements,complex air-flows,maneuvering flight of transport...This article investigates the approaching control for fixed-wing Unmanned Aerial Vehi-cle(UAV)aerial recovery in the presence of pre-specified performance requirements,complex air-flows,maneuvering flight of transport aircraft,and different initial deviations.First,a novelcontrol-oriented Six-Degree-Of-Freedom(6-DOF)UAV model considering airflow disturbancesis established for better consistency with the actual UAV system.Then,to achieve satisfactory per-formance in the approaching process,a Flexible Appointed-time Prescribed Performance Control(FAPPC)algorithm,with the features of user-specified time convergence,no overshoot,indepen-dence from the initial value,and singularity-free,is proposed.Specifically,to solve the singularityissue encountered by the existing PPC methods in dealing with sudden disturbances,an adaptiveadjustment signal is introduced in FAPPC to perceive the threat of increasing error and relax thepreset boundaries appropriately.Moreover,minimum learning parameter-based neural networkestimators are developed to approximate unknown lumped disturbances at a low computationalcost.Finally,the stability of the closed system is analyzed via Lyapunov synthesis,and the effective-ness and advantages of the proposed control scheme are demonstrated via simulation andHardware-In-the-Loop(HIL)experimental validation.展开更多
Inspired by the collective behaviors observed in bird flocks and fish schools,this paper proposes a novel Decentralized Model Predictive Flocking Control(DMPFC)framework to enable UAV swarms to autonomously track pred...Inspired by the collective behaviors observed in bird flocks and fish schools,this paper proposes a novel Decentralized Model Predictive Flocking Control(DMPFC)framework to enable UAV swarms to autonomously track predefined reference trajectories while avoiding collisions and maintaining a stable quasi[Math Processing Error]-lattice formation.Unlike traditional approaches that rely on switching between predefined swarm formations,this framework utilizes identical local interaction rules for each UAV,allowing them to dynamically adjust their control inputs based on the motion states of neighboring UAVs,external environmental factors,and the desired reference trajectory,thereby enabling the swarm to adapt its formation dynamically.Through iterative state updates,the UAVs achieve consensus,allowing the swarm to follow the reference trajectory while self-organizing into a cohesive and stable group structure.To enhance computational efficiency,the framework integrates a closed-form solution for the optimization process,enabling real-time implementation even on computationally constrained micro-quadrotors.Theoretical analysis demonstrates that the proposed method ensures swarm consensus,maintains desired inter-agent distances,and stabilizes the swarm formation.Extensive simulations and real-world experiments validate the approach’s effectiveness and practicality,demonstrating that the proposed method achieves velocity consensus within approximately 200 ms and forms a stable quasi[Math Processing Error]-lattice structure nearly ten times faster than traditional models,with trajectory tracking errors on the order of millimeters.This underscores its potential for robust and efficient UAV swarm coordination in complex scenarios.展开更多
This paper proposes a portable broadband high-gain antenna for unmanned aerial vehicle(UAV)low-altitude control,operating within the dedicated remotely piloted aircraft system(RPAS)band(5.03–5.91 GHz).The total size ...This paper proposes a portable broadband high-gain antenna for unmanned aerial vehicle(UAV)low-altitude control,operating within the dedicated remotely piloted aircraft system(RPAS)band(5.03–5.91 GHz).The total size of the antenna is 240×240×187 mm3.It uses a printed log-periodic dipole antenna(PLPDA)as feed,and a four-layer frequency selective surface(FSS)cascaded as radome to enhance gain.Experimental results demonstrate that the antenna gain ranges from 10.1 to 15.9 dB and the half-power beam width(HPBW,2θ0.5)<23°within the operation band.Compared to existing portable UAV low-altitude control systems,the proposed antenna achieves an average gain enhancement of 4.7 dB.展开更多
An attempt is made to apply modern control technology to the roll and yaw control of a rudderless quad-tiltrotor Unmanned Aerial Vehicle(UAV)in the latter part of the flight mode transition,where aerodynamic forces on...An attempt is made to apply modern control technology to the roll and yaw control of a rudderless quad-tiltrotor Unmanned Aerial Vehicle(UAV)in the latter part of the flight mode transition,where aerodynamic forces on the tiltrotor’s wings start to take effect.A predictor-based adaptive roll and yaw controller is designed to compensate for system uncertainties and parameter changes.A dynamics model of the tiltrotor is built.A Radial-Basis Function(RBF)neural network and offline adaptation method are used to reduce flight controller workload and cope with the nonlinearities in the controls.Simulations are conducted to verify the reference model response tracking and yaw-roll control decoupling ability of the adaptive controller,as well as the validity of the offline adaptation method.Flight tests are conducted to confirm the ability of the adaptive controller to track different roll and yaw reference model responses.The decoupling of roll and yaw controls is also tested in flight via coordinated turn maneuvers with different rotor tilt angles.展开更多
Tradeoff analysis of the factors,including external environment and unmanned aerial vehicle(UAV)aerodynamic attributes,which affect longitudinal carrier landing performance,is important for small UAV.First,small UAV l...Tradeoff analysis of the factors,including external environment and unmanned aerial vehicle(UAV)aerodynamic attributes,which affect longitudinal carrier landing performance,is important for small UAV.First,small UAV longitudinal carrier landing system is established,as well as the nonlinear dynamics and kinematics model,and then the longitudinal flight control system using backstepping technology with minimum information about the aerodynamic is designed.To assess the landing performance,a variety of influencing factors are considered,resulting in the constraints of aerodynamic attributes of carrier UAV.The simulation results show that the severe sea condition has the greatest influence on landing dispersion,while air wake is the primary factor on impact velocity.Among the longitudinal aerodynamic parameters,the lift curve slope is the most important factor affecting the landing performance,and increasing lift curve slope can improve the landing performance significantly.A better system performance will be achieved when the lift curve slope is larger than 2per radian.展开更多
The airborne base station(ABS) can provide wireless coverage to the ground in unmanned aerial vehicle(UAV) cellular networks.When mobile users move among adjacent ABSs,the measurement information reported by a single ...The airborne base station(ABS) can provide wireless coverage to the ground in unmanned aerial vehicle(UAV) cellular networks.When mobile users move among adjacent ABSs,the measurement information reported by a single mobile user is used to trigger the handover mechanism.This handover mechanism lacks the consideration of movement state of mobile users and the location relationship between mobile users,which may lead to handover misjudgments and even communication interrupts.In this paper,we propose an intelligent handover control method in UAV cellular networks.Firstly,we introduce a deep learning model to predict the user trajectories.This prediction model learns the movement behavior of mobile users from the measurement information and analyzes the positional relations between mobile users such as avoiding collision and accommodating fellow pedestrians.Secondly,we propose a handover decision method,which can calculate the users' corresponding receiving power based on the predicted location and the characteristic of air-to-ground channel,to make handover decisions accurately.Finally,we use realistic data sets with thousands of non-linear trajectories to verify the basic functions and performance of our proposed intelligent handover controlmethod.The simulation results show that the handover success rate of the proposed method is 8% higher than existing methods.展开更多
The paper proposes a Virtual Target Guidance(VTG)-based distributed Model Predictive Control(MPC) scheme for formation control of multiple Unmanned Aerial Vehicles(UAVs).First, a framework of distributed MPC scheme is...The paper proposes a Virtual Target Guidance(VTG)-based distributed Model Predictive Control(MPC) scheme for formation control of multiple Unmanned Aerial Vehicles(UAVs).First, a framework of distributed MPC scheme is designed in which each UAV only shares the information with its neighbors, and the obtained local Finite-Horizon Optimal Control Problem(FHOCP) can be solved by swarm intelligent optimization algorithm.Then, a VTG approach is developed and integrated into the distributed MPC scheme to achieve trajectory tracking and obstacle avoidance.Further, an event-triggered mechanism is proposed to reduce the computational burden for UAV formation control, which takes into consideration the predictive state errors as well as the convergence of cost function.Numerical simulations show that the proposed VTG-based distributed MPC scheme is more computationally efficient to achieve formation control of multiple UAVs in comparison with the traditional distributed MPC method.展开更多
This paper discusses the design and software-in-theloop implementation of adaptive formation controllers for fixedwing unmanned aerial vehicles(UAVs) with parametric uncertainty in their structure, namely uncertain ma...This paper discusses the design and software-in-theloop implementation of adaptive formation controllers for fixedwing unmanned aerial vehicles(UAVs) with parametric uncertainty in their structure, namely uncertain mass and inertia. In fact, when aiming at autonomous flight, such parameters cannot assumed to be known as they might vary during the mission(e.g.depending on the payload). Modeling and autopilot design for such autonomous fixed-wing UAVs are presented. The modeling is implemented in Matlab, while the autopilot is based on ArduPilot, a popular open-source autopilot suite. Specifically, the ArduP ilot functionalities are emulated in Matlab according to the Ardupilot documentation and code, which allows us to perform software-in-the-loop simulations of teams of UAVs embedded with actual autopilot protocols. An overview of realtime path planning, trajectory tracking and formation control resulting from the proposed platform is given. The software-inthe-loop simulations show the capability of achieving different UAV formations while handling uncertain mass and inertia.展开更多
In this paper,periodic event-triggered formation control problems with collision avoidance are studied for leader–follower multiple Unmanned Aerial Vehicles(UAVs).Firstly,based on the Artificial Potential Field(APF)m...In this paper,periodic event-triggered formation control problems with collision avoidance are studied for leader–follower multiple Unmanned Aerial Vehicles(UAVs).Firstly,based on the Artificial Potential Field(APF)method,a novel sliding manifold is proposed for controller design,which can solve the problem of collision avoidance.Then,the event-triggered strategy is applied to the distributed formation control of multi-UAV systems,where the evaluation of the event condition is continuous.In addition,the exclusion of Zeno behavior can be guaranteed by the inter-event time between two successive trigger events have a positive lower bound.Next,a periodic event-triggered mechanism is developed for formation control based on the continuous eventtriggered mechanism.The periodic trigger mechanism does not need additional hardware circuits and sophisticated sensors,which can reduce the control cost.The stability of the control system is proved by the Lyapunov function method.Finally,some numerical simulations are presented to illustrate the effectiveness of the proposed control protocol.展开更多
This paper introduces a fault-tolerant control(FTC)design for a faulty fixed-wing unmanned aerial vehicle(UAV).To constrain tracking errors against actuator faults,error constraint inequalities are first transformed t...This paper introduces a fault-tolerant control(FTC)design for a faulty fixed-wing unmanned aerial vehicle(UAV).To constrain tracking errors against actuator faults,error constraint inequalities are first transformed to a new set of variables based on prescribed performance functions.Then,the commonly used and powerful proportional-integral-derivative(PID)control concept is employed to filter the transformed error variables.To handle the fault-induced nonlinear terms,a composite learning algorithm consisting of neural network and disturbance observer is incorporated for increasing flight safety.It is shown by Lyapunov stability analysis that the tracking errors are strictly constrained within the specified error bounds.Experimental results are presented to verify the feasibility of the developed FTC scheme.展开更多
Unmanned Aerial Vehicles(UAVs)enabled Aerial Base Stations(UABSs)have been studied widely in future communications.However,there are a series of challenges such as interference management,trajectory design and resourc...Unmanned Aerial Vehicles(UAVs)enabled Aerial Base Stations(UABSs)have been studied widely in future communications.However,there are a series of challenges such as interference management,trajectory design and resource allocation in the scenarios of multi-UAV networks.Besides,different performances among UABSs increase complexity and bring many challenges.In this paper,the joint downlink transmission power control and trajectory design problem in multi-type UABSs communication network is investigated.In order to satisfy the signal to interference plus noise power ratio of users,each UABS needs to adjust its position and transmission power.Based on the interactions among multiple communication links,a non-cooperative Mean-Field-Type Game(MFTG)is proposed to model the joint optimization problem.Then,a Nash equilibrium solution is solved by two steps:first,the users in the given area are clustered to get the initial deployment of the UABSs;second,the Mean-Field Q(MFQ)-learning algorithm is proposed to solve the discrete MFTG problem.Finally,the effectiveness of the approach is verified through the simulations,which simplifies the solution process and effectively reduces the energy consumption of each UABS.展开更多
This paper proposes a new distributed coordinated control scheme based on heterogeneous roles for Unmanned Aerial Vehicle(UAV)swarm to achieve formation control.First,the framework of the distributed coordinated contr...This paper proposes a new distributed coordinated control scheme based on heterogeneous roles for Unmanned Aerial Vehicle(UAV)swarm to achieve formation control.First,the framework of the distributed coordinated control scheme is designed on the basis of Distributed Model Predictive Control(DMPC).Then,the effect of heterogeneous roles including leader,coordinator and follower is discussed,and the role-based cost functions are developed to improve the performance of coordinated control for UAV swarm.Furthermore,a group of coordination strategies are proposed for UAVs with different roles to achieve swarm conflict resolution.Numerical simulations demonstrate that the presented distributed coordinated control scheme is effective to formulate and maintain the desired formation for the UAV swarm.展开更多
The mathematical model of quadcopter-unmanned aerial vehicle （UAV） is derived by using two approaches： One is the Newton-Euler approach which is formulated using classical meehanics; and other is the Euler-Lagrange...The mathematical model of quadcopter-unmanned aerial vehicle （UAV） is derived by using two approaches： One is the Newton-Euler approach which is formulated using classical meehanics; and other is the Euler-Lagrange approach which describes the model in terms of kinetic （translational and rotational） and potential energy. The proposed quadcopter＇s non-linear model is incorporated with aero-dynamical forces generated by air resistance, which helps aircraft to exhibits more realistic behavior while hovering. Based on the obtained model, the suitable control strategy is developed, under which two effective flight control systems are developed. Each control system is created by cascading the proportional-derivative （PD） and T-S fuzzy controllers that are equipped with six and twelve feedback signals individually respectively to ensure better tracking, stabilization, and response. Both pro- posed flight control designs are then implemented with the quadcopter model respectively and multitudinous simulations are conducted using MATLAB/Simulink to analyze the tracking performance of the quadcopter model at various reference inputs and trajectories.展开更多
基金co-supported by the National Natural Science Foundation of China(No.61903350)the Ministry of Education industry-university-research innovation project,China(No.2021ZYA02002)the Beijing Institute of Technology Research Fund Program for Young Scholars,China(No.3010011182130)。
文摘Unmanned Aerial Vehicle(UAV)swarm collaboration enhances mission effectiveness.However,fixed-wing UAV swarm flights face collaborative safety control problems within a limited airspace in complex environments.Aimed at the cooperative control problem of fixed-wing UAV swarm flights under the airspace constraints of a virtual tube in a complex environment,this paper proposes a behavior-based distributed control method for fixed-wing UAV swarm considering flight safety constraints.Considering the fixed-wing UAV swarm flight problem in complex environment,a virtual tube model based on generator curve is established.The tube keeping,centerline tracking and flight safety behavioral control strategies of the UAV swarm are designed to ensure that the UAV swarm flies along the inside of the virtual tube safety and does not go beyond its boundary.On this basis,a maneuvering decision-making method based on behavioral fusion is proposed to ensure the safe flight of UAV swarm in the restricted airspace.This cooperative control method eliminates the need for respective pre-planned trajectories,reduces communication requirements,and achieves a high level of intelligence.Simulation results show that the proposed behaviorbased UAV swarm cooperative control method is able to make the fixed-wing UAV swarm,which is faster and unable to hover,fly along the virtual tube airspace under various virtual tube shapes and different swarm sizes,and the spacing between the UAVs is larger than the minimum safe distance during the flight.
文摘Recently,unmanned aerial vehicle(UAV)-aided free-space optical(FSO)communication has attracted widespread attentions.However,most of the existing research focuses on communication performance only.The authors investigate the integrated scheduling of communication,sensing,and control for UAV-aided FSO communication systems.Initially,a sensing-control model is established via the control theory.Moreover,an FSO communication channel model is established by considering the effects of atmospheric loss,atmospheric turbulence,geometrical loss,and angle-of-arrival fluctuation.Then,the relationship between the motion control of the UAV and radial displacement is obtained to link the control aspect and communication aspect.Assuming that the base station has instantaneous channel state information(CSI)or statistical CSI,the thresholds of the sensing-control pattern activation are designed,respectively.Finally,an integrated scheduling scheme for performing communication,sensing,and control is proposed.Numerical results indicate that,compared with conventional time-triggered scheme,the proposed integrated scheduling scheme obtains comparable communication and control performance,but reduces the sensing consumed power by 52.46%.
文摘This paper proposes a distributed event-triggered control(ETC)framework to address cooperative target fencing challenges in UAV swarm.The proposed architecture eliminates the reliance on preset formation parameters while achieving multi-objective cooperative control for target fencing,network connectivity preservation,collision avoidance,and communication efficiency optimization.Firstly,a differential state observer is constructed to obtain the target's unmeasurable states.Secondly,leveraging swarm selforganization principles,a geometric-constraint-free distributed fencing controller is designed by integrating potential field methods with consensus theory.The controller dynamically adjusts inter-UAV distances via single potential function,enabling coordinated optimization of persistent network connectivity and collision-free motion during target fencing.Thirdly,a dual-threshold ETC mechanism based on velocity consensus deviation and fencing error is proposed,which can be triggered based on task features to dynamically adjust the communication frequency,significantly reduce the communication burden and exclude Zeno behavior.Theoretical analysis demonstrates the stability of closed-loop systems.Multi-scenario simulations show that the proposed method can achieve robust fencing under target maneuverability,partial UAV failures,and communication disturbances.
基金supported in part by the National Natural Science Foundation of China(62373302,62333009,61973253,62273283).
文摘The maneuvering of a large-scale unmanned aerial vehicle(UAV)swarm,notable for flexible flight with collisionfree,is still challenging due to the significant number of UAVs and the compact configuration of the swarm.In light of this problem,a novel parallel control method that utilizes space and time transformation is proposed.First,the swarm is decomposed based on a grouping-hierarchical strategy,while the distinct flight roles are assigned to each UAV.Then,to achieve the desired configuration(DCF)in the real world,a bijection transformation is conducted in the space domain,converting an arbitrarily general configuration(GCF)into a standard configuration(SCF)in the virtual space.Further,to improve the flexibility of the swarm,the time scaling transformation is adopted in the time domain,which ensures the desired prescribed-time convergence of the swarm independent of initial conditions.Finally,simulation results demonstrate that collision-free maneuvering,including formation changes and turning,can be effectively and rapidly achieved by the proposed parallel control method.Overall,this research contributes a viable solution for enhancing cooperation among largescale UAV swarms.
基金funded by the National Natural Science Foundation of China(Nos.62173022,61673042)the Academic Excellence Foundation of Beihang University for Ph.D.Studentsthe Outstanding Research Project of Shen Yuan Honors College,Beihang University,China(No.230123104)。
文摘This article investigates the approaching control for fixed-wing Unmanned Aerial Vehi-cle(UAV)aerial recovery in the presence of pre-specified performance requirements,complex air-flows,maneuvering flight of transport aircraft,and different initial deviations.First,a novelcontrol-oriented Six-Degree-Of-Freedom(6-DOF)UAV model considering airflow disturbancesis established for better consistency with the actual UAV system.Then,to achieve satisfactory per-formance in the approaching process,a Flexible Appointed-time Prescribed Performance Control(FAPPC)algorithm,with the features of user-specified time convergence,no overshoot,indepen-dence from the initial value,and singularity-free,is proposed.Specifically,to solve the singularityissue encountered by the existing PPC methods in dealing with sudden disturbances,an adaptiveadjustment signal is introduced in FAPPC to perceive the threat of increasing error and relax thepreset boundaries appropriately.Moreover,minimum learning parameter-based neural networkestimators are developed to approximate unknown lumped disturbances at a low computationalcost.Finally,the stability of the closed system is analyzed via Lyapunov synthesis,and the effective-ness and advantages of the proposed control scheme are demonstrated via simulation andHardware-In-the-Loop(HIL)experimental validation.
基金supported in part by the Guangdong Provincial Universities'Characteristic Innovation Project under Grant 2024KTSCX360in part by the Guangdong Educational Science Planning Project under Grant 2023GXJK837.
文摘Inspired by the collective behaviors observed in bird flocks and fish schools,this paper proposes a novel Decentralized Model Predictive Flocking Control(DMPFC)framework to enable UAV swarms to autonomously track predefined reference trajectories while avoiding collisions and maintaining a stable quasi[Math Processing Error]-lattice formation.Unlike traditional approaches that rely on switching between predefined swarm formations,this framework utilizes identical local interaction rules for each UAV,allowing them to dynamically adjust their control inputs based on the motion states of neighboring UAVs,external environmental factors,and the desired reference trajectory,thereby enabling the swarm to adapt its formation dynamically.Through iterative state updates,the UAVs achieve consensus,allowing the swarm to follow the reference trajectory while self-organizing into a cohesive and stable group structure.To enhance computational efficiency,the framework integrates a closed-form solution for the optimization process,enabling real-time implementation even on computationally constrained micro-quadrotors.Theoretical analysis demonstrates that the proposed method ensures swarm consensus,maintains desired inter-agent distances,and stabilizes the swarm formation.Extensive simulations and real-world experiments validate the approach’s effectiveness and practicality,demonstrating that the proposed method achieves velocity consensus within approximately 200 ms and forms a stable quasi[Math Processing Error]-lattice structure nearly ten times faster than traditional models,with trajectory tracking errors on the order of millimeters.This underscores its potential for robust and efficient UAV swarm coordination in complex scenarios.
文摘This paper proposes a portable broadband high-gain antenna for unmanned aerial vehicle(UAV)low-altitude control,operating within the dedicated remotely piloted aircraft system(RPAS)band(5.03–5.91 GHz).The total size of the antenna is 240×240×187 mm3.It uses a printed log-periodic dipole antenna(PLPDA)as feed,and a four-layer frequency selective surface(FSS)cascaded as radome to enhance gain.Experimental results demonstrate that the antenna gain ranges from 10.1 to 15.9 dB and the half-power beam width(HPBW,2θ0.5)<23°within the operation band.Compared to existing portable UAV low-altitude control systems,the proposed antenna achieves an average gain enhancement of 4.7 dB.
文摘An attempt is made to apply modern control technology to the roll and yaw control of a rudderless quad-tiltrotor Unmanned Aerial Vehicle(UAV)in the latter part of the flight mode transition,where aerodynamic forces on the tiltrotor’s wings start to take effect.A predictor-based adaptive roll and yaw controller is designed to compensate for system uncertainties and parameter changes.A dynamics model of the tiltrotor is built.A Radial-Basis Function(RBF)neural network and offline adaptation method are used to reduce flight controller workload and cope with the nonlinearities in the controls.Simulations are conducted to verify the reference model response tracking and yaw-roll control decoupling ability of the adaptive controller,as well as the validity of the offline adaptation method.Flight tests are conducted to confirm the ability of the adaptive controller to track different roll and yaw reference model responses.The decoupling of roll and yaw controls is also tested in flight via coordinated turn maneuvers with different rotor tilt angles.
基金supported by the National Nature Science Foundation of China(61304223)the Aeronautical Science Foundation of China(2016ZA52009)the Research Fund for the Doctoral Program of Higher Education of China(20123218120015)
基金supported by the National Nature Science Foundation of China(Nos.61304223,61403197)the Aeronautical Science Foundation of China(No.2013ZA52002)the Research Fund for the Doctoral Program of Higher Education of China(No.20123218120015)
文摘Tradeoff analysis of the factors,including external environment and unmanned aerial vehicle(UAV)aerodynamic attributes,which affect longitudinal carrier landing performance,is important for small UAV.First,small UAV longitudinal carrier landing system is established,as well as the nonlinear dynamics and kinematics model,and then the longitudinal flight control system using backstepping technology with minimum information about the aerodynamic is designed.To assess the landing performance,a variety of influencing factors are considered,resulting in the constraints of aerodynamic attributes of carrier UAV.The simulation results show that the severe sea condition has the greatest influence on landing dispersion,while air wake is the primary factor on impact velocity.Among the longitudinal aerodynamic parameters,the lift curve slope is the most important factor affecting the landing performance,and increasing lift curve slope can improve the landing performance significantly.A better system performance will be achieved when the lift curve slope is larger than 2per radian.
基金supported in parts by the National Natural Science Foundation of China for Distinguished Young Scholar under Grant 61425012the National Science and Technology Major Projects for the New Generation of Broadband Wireless Communication Network under Grant 2017ZX03001014
文摘The airborne base station(ABS) can provide wireless coverage to the ground in unmanned aerial vehicle(UAV) cellular networks.When mobile users move among adjacent ABSs,the measurement information reported by a single mobile user is used to trigger the handover mechanism.This handover mechanism lacks the consideration of movement state of mobile users and the location relationship between mobile users,which may lead to handover misjudgments and even communication interrupts.In this paper,we propose an intelligent handover control method in UAV cellular networks.Firstly,we introduce a deep learning model to predict the user trajectories.This prediction model learns the movement behavior of mobile users from the measurement information and analyzes the positional relations between mobile users such as avoiding collision and accommodating fellow pedestrians.Secondly,we propose a handover decision method,which can calculate the users' corresponding receiving power based on the predicted location and the characteristic of air-to-ground channel,to make handover decisions accurately.Finally,we use realistic data sets with thousands of non-linear trajectories to verify the basic functions and performance of our proposed intelligent handover controlmethod.The simulation results show that the handover success rate of the proposed method is 8% higher than existing methods.
基金supported by National Natural Science Foundation of China(61174102)Jiangsu Natural Science Foundation of China(SBK20130033)+1 种基金Aeronautical Science Foundation of China 20145152029)Specialized Research Fund for the Doctoral Program of Higher Education(20133218110013)
基金supported in part by the National Natural Science Foundation of China(No.61803009)Fundamental Research Funds for the Central Universities,China(No.YWF-19-BJ-J-205)Aeronautical Science Foundation of China(No.20175851032)。
文摘The paper proposes a Virtual Target Guidance(VTG)-based distributed Model Predictive Control(MPC) scheme for formation control of multiple Unmanned Aerial Vehicles(UAVs).First, a framework of distributed MPC scheme is designed in which each UAV only shares the information with its neighbors, and the obtained local Finite-Horizon Optimal Control Problem(FHOCP) can be solved by swarm intelligent optimization algorithm.Then, a VTG approach is developed and integrated into the distributed MPC scheme to achieve trajectory tracking and obstacle avoidance.Further, an event-triggered mechanism is proposed to reduce the computational burden for UAV formation control, which takes into consideration the predictive state errors as well as the convergence of cost function.Numerical simulations show that the proposed VTG-based distributed MPC scheme is more computationally efficient to achieve formation control of multiple UAVs in comparison with the traditional distributed MPC method.
基金supported by the Fundamental Research Funds for the Central Universities(4007019109)(RECON-STRUCT)the Special Guiding Funds for Double First-class(4007019201)the Joint TU Delft-CSSC Project ‘Multi-agent Coordination with Networked Constraints’(MULTI-COORD)
文摘This paper discusses the design and software-in-theloop implementation of adaptive formation controllers for fixedwing unmanned aerial vehicles(UAVs) with parametric uncertainty in their structure, namely uncertain mass and inertia. In fact, when aiming at autonomous flight, such parameters cannot assumed to be known as they might vary during the mission(e.g.depending on the payload). Modeling and autopilot design for such autonomous fixed-wing UAVs are presented. The modeling is implemented in Matlab, while the autopilot is based on ArduPilot, a popular open-source autopilot suite. Specifically, the ArduP ilot functionalities are emulated in Matlab according to the Ardupilot documentation and code, which allows us to perform software-in-the-loop simulations of teams of UAVs embedded with actual autopilot protocols. An overview of realtime path planning, trajectory tracking and formation control resulting from the proposed platform is given. The software-inthe-loop simulations show the capability of achieving different UAV formations while handling uncertain mass and inertia.
基金supported in part by the Foundation(No.2019-JCJQ-ZD-049)the National Natural Science Foundation of China(Nos.61703134,62022060,62073234,61773278)+2 种基金The China Postdoctoral Science Foundation(No.2019M650874)The Key R&D Program of Hebei Province(No.20310802D)the Natural Science Foundation of Hebei Province(Nos.F2019202369,F2018202279,F2019202363)。
文摘In this paper,periodic event-triggered formation control problems with collision avoidance are studied for leader–follower multiple Unmanned Aerial Vehicles(UAVs).Firstly,based on the Artificial Potential Field(APF)method,a novel sliding manifold is proposed for controller design,which can solve the problem of collision avoidance.Then,the event-triggered strategy is applied to the distributed formation control of multi-UAV systems,where the evaluation of the event condition is continuous.In addition,the exclusion of Zeno behavior can be guaranteed by the inter-event time between two successive trigger events have a positive lower bound.Next,a periodic event-triggered mechanism is developed for formation control based on the continuous eventtriggered mechanism.The periodic trigger mechanism does not need additional hardware circuits and sophisticated sensors,which can reduce the control cost.The stability of the control system is proved by the Lyapunov function method.Finally,some numerical simulations are presented to illustrate the effectiveness of the proposed control protocol.
基金This work was supported by the National Natural Science Foundation of China(62003162,61833013,62020106003)the Natural Science Foundation of Jiangsu Province of China(BK20200416)+3 种基金the China Postdoctoral Science Foundation(2020TQ0151,2020M681590)the State Key Laboratory of Synthetical Automation for Process Industries,Northeastern University(2019-KF-23-05)the 111 Project(B20007)the Natural Sciences and Engineering Research Council of Canada.
文摘This paper introduces a fault-tolerant control(FTC)design for a faulty fixed-wing unmanned aerial vehicle(UAV).To constrain tracking errors against actuator faults,error constraint inequalities are first transformed to a new set of variables based on prescribed performance functions.Then,the commonly used and powerful proportional-integral-derivative(PID)control concept is employed to filter the transformed error variables.To handle the fault-induced nonlinear terms,a composite learning algorithm consisting of neural network and disturbance observer is incorporated for increasing flight safety.It is shown by Lyapunov stability analysis that the tracking errors are strictly constrained within the specified error bounds.Experimental results are presented to verify the feasibility of the developed FTC scheme.
基金co-supported by the National Natural Science Foundation of China(Nos.62001387,61901379)the Natural Science Basic Research Plan in Shaanxi Province(No.2019JQ253)+4 种基金the Key R&D Plan of Shaanxi Province(No.2020GY034)the Aerospace Science and Technology Innovation Fund of China Aerospace Science and Technology Corporationthe Shanghai Aerospace Science and Technology Innovation Fund(No.SAST2018045)the China Fundamental Research Fund for the Central Universities(No.3102018QD096)the Seed Foundation of Innovation and Creation for Graduate Students in Northwestern Polytechnical University(No.CX2020152)。
文摘Unmanned Aerial Vehicles(UAVs)enabled Aerial Base Stations(UABSs)have been studied widely in future communications.However,there are a series of challenges such as interference management,trajectory design and resource allocation in the scenarios of multi-UAV networks.Besides,different performances among UABSs increase complexity and bring many challenges.In this paper,the joint downlink transmission power control and trajectory design problem in multi-type UABSs communication network is investigated.In order to satisfy the signal to interference plus noise power ratio of users,each UABS needs to adjust its position and transmission power.Based on the interactions among multiple communication links,a non-cooperative Mean-Field-Type Game(MFTG)is proposed to model the joint optimization problem.Then,a Nash equilibrium solution is solved by two steps:first,the users in the given area are clustered to get the initial deployment of the UABSs;second,the Mean-Field Q(MFQ)-learning algorithm is proposed to solve the discrete MFTG problem.Finally,the effectiveness of the approach is verified through the simulations,which simplifies the solution process and effectively reduces the energy consumption of each UABS.
基金co-supported by the National Natural Science Foundation of China(Nos.61803009,61903084)Fundamental Research Funds for the Central Universities of China(No.YWF-20-BJ-J-542)the National Science Foundation of Jiangsu Province,China(No.BK20180358).
文摘This paper proposes a new distributed coordinated control scheme based on heterogeneous roles for Unmanned Aerial Vehicle(UAV)swarm to achieve formation control.First,the framework of the distributed coordinated control scheme is designed on the basis of Distributed Model Predictive Control(DMPC).Then,the effect of heterogeneous roles including leader,coordinator and follower is discussed,and the role-based cost functions are developed to improve the performance of coordinated control for UAV swarm.Furthermore,a group of coordination strategies are proposed for UAVs with different roles to achieve swarm conflict resolution.Numerical simulations demonstrate that the presented distributed coordinated control scheme is effective to formulate and maintain the desired formation for the UAV swarm.
基金supported by the National Natural Science Foundation of China(Nos.61673209,61741313,61304223)the Aeronautical Science Foundation(Nos.2016ZA52009)+1 种基金the Jiangsu Six Peak of Talents Program(No.KTHY-027)the Fundamental Research Funds for the Central Universities(Nos.NJ20160026,NS2017015)
文摘The mathematical model of quadcopter-unmanned aerial vehicle （UAV） is derived by using two approaches： One is the Newton-Euler approach which is formulated using classical meehanics; and other is the Euler-Lagrange approach which describes the model in terms of kinetic （translational and rotational） and potential energy. The proposed quadcopter＇s non-linear model is incorporated with aero-dynamical forces generated by air resistance, which helps aircraft to exhibits more realistic behavior while hovering. Based on the obtained model, the suitable control strategy is developed, under which two effective flight control systems are developed. Each control system is created by cascading the proportional-derivative （PD） and T-S fuzzy controllers that are equipped with six and twelve feedback signals individually respectively to ensure better tracking, stabilization, and response. Both pro- posed flight control designs are then implemented with the quadcopter model respectively and multitudinous simulations are conducted using MATLAB/Simulink to analyze the tracking performance of the quadcopter model at various reference inputs and trajectories.
