The paper presents a two-layer,disturbance-resistant,and fault-tolerant affine formation maneuver control scheme that accomplishes the surrounding of a dynamic target with multiple underactuated Quadrotor Unmanned Aer...The paper presents a two-layer,disturbance-resistant,and fault-tolerant affine formation maneuver control scheme that accomplishes the surrounding of a dynamic target with multiple underactuated Quadrotor Unmanned Aerial Vehicles(QUAVs).This scheme mainly consists of predefinedtime estimators and fixed-time tracking controllers,with a hybrid Laplacian matrix describing the communication among these QUAVs.At the first layer,we devise predefined time estimators for leading and following QUAVs,enabling accurate estimation of desired information.In the second layer,we initially devise a fixed-time hybrid observer to estimate unknown disturbances and actuator faults.Fixedtime translational tracking controllers are then proposed,and the intermediary control input from these controllers is used to extract the desired attitude and angular velocities for the fixed-time rotational tracking controllers.We employ an exact tracking differentiator to handle variables that are challenging to differentiate directly.The paper includes a demonstration of the control system stability through mathematical proof,as well as the presentation of simulation results and comparative simulations.展开更多
This paper addresses a target-enclosing problem for multiple spacecraft systems by proposing a two-layer affine formation control strategy. Compared with the existing methods,the adopted two-layer network structure in...This paper addresses a target-enclosing problem for multiple spacecraft systems by proposing a two-layer affine formation control strategy. Compared with the existing methods,the adopted two-layer network structure in this paper is generally directed, which is suitable for practical space missions. Firstly, distributed finite-time sliding-mode estimators and formation controllers in both layers are designed separately to improve the flexibility of the formation control system. By introducing the properties of affine transformation into formation control protocol design,the controllers can be used to track different time-varying target formation patterns. Besides, multilayer time-varying encirclements can be achieved with particular shapes to surround the moving target. In the sequel, by integrating adaptive neural networks and specialized artificial potential functions into backstepping controllers, the problems of uncertain Euler-Lagrange models, collision avoidance as well as formation reconfiguration are solved simultaneously. The stability of the proposed controllers is verified by the Lyapunov direct method. Finally, two simulation examples of triangle formation and more complex hexagon formation are presented to illustrate the feasibility of the theoretical results.展开更多
Aiming at the problem of multi-UAV pursuit-evasion confrontation, a UAV cooperative maneuver method based on an improved multi-agent deep reinforcement learning(MADRL) is proposed. In this method, an improved Comm Net...Aiming at the problem of multi-UAV pursuit-evasion confrontation, a UAV cooperative maneuver method based on an improved multi-agent deep reinforcement learning(MADRL) is proposed. In this method, an improved Comm Net network based on a communication mechanism is introduced into a deep reinforcement learning algorithm to solve the multi-agent problem. A layer of gated recurrent unit(GRU) is added to the actor-network structure to remember historical environmental states. Subsequently,another GRU is designed as a communication channel in the Comm Net core network layer to refine communication information between UAVs. Finally, the simulation results of the algorithm in two sets of scenarios are given, and the results show that the method has good effectiveness and applicability.展开更多
In recent years,multi-agent systems(MASs)formation tracking control(FTC)technology has achieved substantial advancements and has become a prominent research area due to its widespread applications in various fields,su...In recent years,multi-agent systems(MASs)formation tracking control(FTC)technology has achieved substantial advancements and has become a prominent research area due to its widespread applications in various fields,such as multi-unmanned aerial vehicle(multi-UAV)systems[1]and multiautonomous underwater vehicle(multi-AUV)systems[2].The consensusbased approach has evolved into the principal method for MASs’FTC because of its advantages,including rigorous logical deduction,easily solvable control parameters,and strong universal performance.展开更多
This article explores the leader-following consensus tracking(LFCK)control issues of multi-agent systems(MASs)in the presence of external disturbances and general directed fixed communication topology.Its purpose is t...This article explores the leader-following consensus tracking(LFCK)control issues of multi-agent systems(MASs)in the presence of external disturbances and general directed fixed communication topology.Its purpose is to enable all follower agents to achieve consensus tracking for the leader agent.Firstly,this article introduces an extended state observer for estimating each follower agent's unknown state and external disturbance.Subsequently,on the basis of the above-extended state observer and a dynamic event-triggered strategy,a distributed consensus tracking control protocol with disturbances restraint is developed,which can reduce the MAS's update frequency on the premise of ensuring the control protocol's effectiveness.Furthermore,the MAS's stability and the absence of Zeno behavior are analyzed and proved by the established Lyapunov functional and linear matrix inequality theory.Finally,the validity and feasibility of the proposed approach are validated through a group of comparative numerical simulation experiments.展开更多
In the field of infrared and visible image fusion,researchers have put increasingly complex fusion networks forward to pursue better fusion metrics.This has led to a growing number of parameters in fusion models.Addit...In the field of infrared and visible image fusion,researchers have put increasingly complex fusion networks forward to pursue better fusion metrics.This has led to a growing number of parameters in fusion models.Additionally,most fusion models rarely address the issue of preserving background details in images,while these details are vital to subsequent advanced visual tasks,such as image analysis and recognition.In response to these limitations mentioned above,this paper proposes a novel image fusion algorithm called lightweight multi-scale hierarchical dense fusion network(LMHFusion).Concisely,we propose a lightweight multi-scale encoder.It extracts multi-scale features from input images through four encoding blocks with different receptive fields.Then,a designed hierarchical dense connection method is employed to concatenate distinct scale features.Unlike traditional manual fusion strategies,our fusion network is designed to be learnable and has adjustable weights.Moreover,we have specially designed a histogram equalization loss to train LMHFusion.This new loss produces fused images that contain both prominent structures and rich details.Through comparative analysis of LMHFusion and twelve other representative fusion models,it has been proven that LMHFusion can make the model more suitable for resource-constrained scenarios apart from enhancing the quality and visual effects of fused images.Our model is nearly 5000 times smaller in size compared to RFN-Nest.展开更多
To identify the unsteady°uid dynamic model for a solid moving in the°uid,a new identication method that operates in the continuous time domain is proposed.It is illustrated that this new identication method ...To identify the unsteady°uid dynamic model for a solid moving in the°uid,a new identication method that operates in the continuous time domain is proposed.It is illustrated that this new identication method is more accurate and appropriate for identifying unsteady°uid dynamic model in incompressible°ow in comparison with the classical frequency domain or discrete domain method.This new method is applied to identify the unsteady°uid dynamic models of a NACA0012 airfoil and the e®ect of the°uid viscosity on the model parameter is analyzed.The result shows that the added mass in viscous°ow is dependent on the input signal frequency and is exactly the added mass in inviscid°ow when the frequency approaches innity.Based on this discovery,the long controversy on the relationship of added mass between viscous and inviscid°ow is solved.Then,the enlightenment of this discovery on the identication of both linear and nonlinear unsteady aerodynamic model in incompressible°ow is illustrated.At last,the advantage of the new acquired unsteady°uid dynamic model is discussed in comparison with the classical quasi-steady aerodynamic model.展开更多
The application of unmanned aerial vehicles(UAVs)poses many technique questions to be addressed urgently in the Guidance,Navigation and Control(GNC)-eld.1,2 Complexities and uncertainties with highly nonlinear dynamic...The application of unmanned aerial vehicles(UAVs)poses many technique questions to be addressed urgently in the Guidance,Navigation and Control(GNC)-eld.1,2 Complexities and uncertainties with highly nonlinear dynamics of UAVs towards practical use environments to various missions and applications are the main issues and challenges being faced for the development of autonomous,intelligent,reliable,safe and low-cost UAVs.With the unceasing and rapid progress made on the electronics,communication,computation,sensing,actuating,control,arti-cial intelligence and machine learning sciences and technologies,great developments have been achieved for UAV towards autonomous,intelligent and safe control technologies in recent years along with enhancement and new development on UAVs'autonomy,intelligence and safety levels.展开更多
Purpose–The purpose of this paper is to develop a monocular visual measurement system for autonomous aerial refueling(AAR)for unmanned aerial vehicle,which can process images from an infrared camera to estimate the p...Purpose–The purpose of this paper is to develop a monocular visual measurement system for autonomous aerial refueling(AAR)for unmanned aerial vehicle,which can process images from an infrared camera to estimate the pose of the drogue in the tanker with high accuracy and real-time performance.Design/methodology/approach–Methods and techniques for marker detection,feature matching and pose estimation have been designed and implemented in the visual measurement system.Findings–The simple blob detection(SBD)method is adopted,which outperforms the Laplacian of Gaussian method.And a novel noise-elimination algorithm is proposed for excluding the noise points.Besides,a novel feature matching algorithm based on perspective transformation is proposed.Comparative experimental results indicated the rapidity and effectiveness of the proposed methods.Practical implications–The visual measurement system developed in this paper can be applied to estimate the pose of the drogue with a fast speed and high accuracy and it is a feasible measurement strategy which will considerably increase the autonomy and reliability for AAR.Originality/value–The SBD method is used to detect the features and a novel noise-elimination algorithm is proposed.Besides,a novel feature matching algorithm based on perspective transformation is proposed which is robust and accurate.展开更多
Autonomous control of Unmanned Aerial System(UAS)is that UASs can make decisions in the flight and carry out missions autonomously according to the scheduled tasks and rules through online sensing the surrounding situ...Autonomous control of Unmanned Aerial System(UAS)is that UASs can make decisions in the flight and carry out missions autonomously according to the scheduled tasks and rules through online sensing the surrounding situation.Through cooperation,UASs can share information among individual agents and work together to accomplish complicated mission which would not be possible for a single agent otherwise.With the development of UAS technology,autonomous control has become one of the hot topics and key technologies in UAS research field.展开更多
基金supported by Natural Science Basic Research Plan in Shaanxi Province of China(No.2023-JC-QN-0733)Guangdong Basic and Applied Basic Research Foundation,China(No.2022A1515110753)+2 种基金China Postdoctoral Science Foundation(No.2022M722583)China Industry-UniversityResearch Innovation Foundation(No.2022IT188)National Key Laboratory of Air-based Information Perception and Fusion and the Aeronautic Science Foundation of China(No.20220001068001)。
文摘The paper presents a two-layer,disturbance-resistant,and fault-tolerant affine formation maneuver control scheme that accomplishes the surrounding of a dynamic target with multiple underactuated Quadrotor Unmanned Aerial Vehicles(QUAVs).This scheme mainly consists of predefinedtime estimators and fixed-time tracking controllers,with a hybrid Laplacian matrix describing the communication among these QUAVs.At the first layer,we devise predefined time estimators for leading and following QUAVs,enabling accurate estimation of desired information.In the second layer,we initially devise a fixed-time hybrid observer to estimate unknown disturbances and actuator faults.Fixedtime translational tracking controllers are then proposed,and the intermediary control input from these controllers is used to extract the desired attitude and angular velocities for the fixed-time rotational tracking controllers.We employ an exact tracking differentiator to handle variables that are challenging to differentiate directly.The paper includes a demonstration of the control system stability through mathematical proof,as well as the presentation of simulation results and comparative simulations.
基金sponsored by National Natural Science Foundation of China (Nos. 61673327, 51606161, 11602209, 91441128)Natural Science Foundation of Fujian Province of China (No. 2016J06011)China Scholarship Council (No. 201606310153)
文摘This paper addresses a target-enclosing problem for multiple spacecraft systems by proposing a two-layer affine formation control strategy. Compared with the existing methods,the adopted two-layer network structure in this paper is generally directed, which is suitable for practical space missions. Firstly, distributed finite-time sliding-mode estimators and formation controllers in both layers are designed separately to improve the flexibility of the formation control system. By introducing the properties of affine transformation into formation control protocol design,the controllers can be used to track different time-varying target formation patterns. Besides, multilayer time-varying encirclements can be achieved with particular shapes to surround the moving target. In the sequel, by integrating adaptive neural networks and specialized artificial potential functions into backstepping controllers, the problems of uncertain Euler-Lagrange models, collision avoidance as well as formation reconfiguration are solved simultaneously. The stability of the proposed controllers is verified by the Lyapunov direct method. Finally, two simulation examples of triangle formation and more complex hexagon formation are presented to illustrate the feasibility of the theoretical results.
基金supported in part by the National Key Laboratory of Air-based Information Perception and Fusion and the Aeronautical Science Foundation of China (Grant No. 20220001068001)National Natural Science Foundation of China (Grant No.61673327)+1 种基金Natural Science Basic Research Plan in Shaanxi Province,China (Grant No. 2023-JC-QN-0733)China IndustryUniversity-Research Innovation Foundation (Grant No. 2022IT188)。
文摘Aiming at the problem of multi-UAV pursuit-evasion confrontation, a UAV cooperative maneuver method based on an improved multi-agent deep reinforcement learning(MADRL) is proposed. In this method, an improved Comm Net network based on a communication mechanism is introduced into a deep reinforcement learning algorithm to solve the multi-agent problem. A layer of gated recurrent unit(GRU) is added to the actor-network structure to remember historical environmental states. Subsequently,another GRU is designed as a communication channel in the Comm Net core network layer to refine communication information between UAVs. Finally, the simulation results of the algorithm in two sets of scenarios are given, and the results show that the method has good effectiveness and applicability.
基金supported by the National Science Fund for Distinguished Young Scholars(62425304)the National Key Laboratory of Air-based Information Perception and Fusion and the Aeronautical Science Foundation of China(Grant No.20220001068001)the Ganzhou Key Laboratory of Smart Integrated Photovoltaic-Charging-Storage Energy System(Grant No.2024YSPT0010)。
文摘In recent years,multi-agent systems(MASs)formation tracking control(FTC)technology has achieved substantial advancements and has become a prominent research area due to its widespread applications in various fields,such as multi-unmanned aerial vehicle(multi-UAV)systems[1]and multiautonomous underwater vehicle(multi-AUV)systems[2].The consensusbased approach has evolved into the principal method for MASs’FTC because of its advantages,including rigorous logical deduction,easily solvable control parameters,and strong universal performance.
基金supported by Guangdong Major Project of Basic and Applied Basic Research(Grant No.2023B0303000016)the National Natural Science Foundation of China(Grant No.U21A20487)+5 种基金Shenzhen Technology Project(Grant Nos.JCYJ20220818101206014,JCYJ20220818101211025)the CAS Key Technology Talent Program,the National Outstanding Youth Talents Support Program(Grant No.61822304)Shanghai Municipal Science and Technology Major Project(Grant No.2021SHZDZX0100)Shanghai Municipal Commission of Science and Technology Project(Grant No.19511132101)the Projects of Major International(Regional)Joint Research Program of NSFC(Grant No.61720106011)the National Natural Science Foundation of China(Grant No.62372440)。
文摘This article explores the leader-following consensus tracking(LFCK)control issues of multi-agent systems(MASs)in the presence of external disturbances and general directed fixed communication topology.Its purpose is to enable all follower agents to achieve consensus tracking for the leader agent.Firstly,this article introduces an extended state observer for estimating each follower agent's unknown state and external disturbance.Subsequently,on the basis of the above-extended state observer and a dynamic event-triggered strategy,a distributed consensus tracking control protocol with disturbances restraint is developed,which can reduce the MAS's update frequency on the premise of ensuring the control protocol's effectiveness.Furthermore,the MAS's stability and the absence of Zeno behavior are analyzed and proved by the established Lyapunov functional and linear matrix inequality theory.Finally,the validity and feasibility of the proposed approach are validated through a group of comparative numerical simulation experiments.
基金supported by the National Key Laboratory of Air-based Information Perception and Fusion and the Aeronautical Science Foundation of China(Grant No.20220001068001)。
文摘In the field of infrared and visible image fusion,researchers have put increasingly complex fusion networks forward to pursue better fusion metrics.This has led to a growing number of parameters in fusion models.Additionally,most fusion models rarely address the issue of preserving background details in images,while these details are vital to subsequent advanced visual tasks,such as image analysis and recognition.In response to these limitations mentioned above,this paper proposes a novel image fusion algorithm called lightweight multi-scale hierarchical dense fusion network(LMHFusion).Concisely,we propose a lightweight multi-scale encoder.It extracts multi-scale features from input images through four encoding blocks with different receptive fields.Then,a designed hierarchical dense connection method is employed to concatenate distinct scale features.Unlike traditional manual fusion strategies,our fusion network is designed to be learnable and has adjustable weights.Moreover,we have specially designed a histogram equalization loss to train LMHFusion.This new loss produces fused images that contain both prominent structures and rich details.Through comparative analysis of LMHFusion and twelve other representative fusion models,it has been proven that LMHFusion can make the model more suitable for resource-constrained scenarios apart from enhancing the quality and visual effects of fused images.Our model is nearly 5000 times smaller in size compared to RFN-Nest.
文摘To identify the unsteady°uid dynamic model for a solid moving in the°uid,a new identication method that operates in the continuous time domain is proposed.It is illustrated that this new identication method is more accurate and appropriate for identifying unsteady°uid dynamic model in incompressible°ow in comparison with the classical frequency domain or discrete domain method.This new method is applied to identify the unsteady°uid dynamic models of a NACA0012 airfoil and the e®ect of the°uid viscosity on the model parameter is analyzed.The result shows that the added mass in viscous°ow is dependent on the input signal frequency and is exactly the added mass in inviscid°ow when the frequency approaches innity.Based on this discovery,the long controversy on the relationship of added mass between viscous and inviscid°ow is solved.Then,the enlightenment of this discovery on the identication of both linear and nonlinear unsteady aerodynamic model in incompressible°ow is illustrated.At last,the advantage of the new acquired unsteady°uid dynamic model is discussed in comparison with the classical quasi-steady aerodynamic model.
文摘The application of unmanned aerial vehicles(UAVs)poses many technique questions to be addressed urgently in the Guidance,Navigation and Control(GNC)-eld.1,2 Complexities and uncertainties with highly nonlinear dynamics of UAVs towards practical use environments to various missions and applications are the main issues and challenges being faced for the development of autonomous,intelligent,reliable,safe and low-cost UAVs.With the unceasing and rapid progress made on the electronics,communication,computation,sensing,actuating,control,arti-cial intelligence and machine learning sciences and technologies,great developments have been achieved for UAV towards autonomous,intelligent and safe control technologies in recent years along with enhancement and new development on UAVs'autonomy,intelligence and safety levels.
基金This research is partially supported by National Natural Science Foundation of China under Grant No.61673327Aeronautical Science Foundation of China under Grant No.20160168001。
文摘Purpose–The purpose of this paper is to develop a monocular visual measurement system for autonomous aerial refueling(AAR)for unmanned aerial vehicle,which can process images from an infrared camera to estimate the pose of the drogue in the tanker with high accuracy and real-time performance.Design/methodology/approach–Methods and techniques for marker detection,feature matching and pose estimation have been designed and implemented in the visual measurement system.Findings–The simple blob detection(SBD)method is adopted,which outperforms the Laplacian of Gaussian method.And a novel noise-elimination algorithm is proposed for excluding the noise points.Besides,a novel feature matching algorithm based on perspective transformation is proposed.Comparative experimental results indicated the rapidity and effectiveness of the proposed methods.Practical implications–The visual measurement system developed in this paper can be applied to estimate the pose of the drogue with a fast speed and high accuracy and it is a feasible measurement strategy which will considerably increase the autonomy and reliability for AAR.Originality/value–The SBD method is used to detect the features and a novel noise-elimination algorithm is proposed.Besides,a novel feature matching algorithm based on perspective transformation is proposed which is robust and accurate.
文摘Autonomous control of Unmanned Aerial System(UAS)is that UASs can make decisions in the flight and carry out missions autonomously according to the scheduled tasks and rules through online sensing the surrounding situation.Through cooperation,UASs can share information among individual agents and work together to accomplish complicated mission which would not be possible for a single agent otherwise.With the development of UAS technology,autonomous control has become one of the hot topics and key technologies in UAS research field.
