Formation control of multiple spacecraft has attracted extensive research attention.However,achieving reliable performance under sensor failures remains a significant challenge.This paper develops an integrated framew...Formation control of multiple spacecraft has attracted extensive research attention.However,achieving reliable performance under sensor failures remains a significant challenge.This paper develops an integrated framework that jointly designs distributed observers and local controllers to ensure robust formation control in the presence of external disturbances and sensor malfunctions.Treating the spacecraft formation as a single interconnected system,each spacecraft constructs a distributed observer that estimates the overall system state by incorporating both its own measurements and the predicted control information shared among the spacecraft.Based on the observer estimates,a local control law is synthesized to maintain the desired formation.Rigorous theoretical analysis and numerical simulations demonstrate that the proposed integrated approach effectively guarantees formation stability and resilience against sensor failures and disturbances.展开更多
Researchers are increasingly focused on enabling groups of multiple unmanned vehicles to operate cohesively in complex,real-world environments,where coordinated formation control and obstacle avoidance are essential f...Researchers are increasingly focused on enabling groups of multiple unmanned vehicles to operate cohesively in complex,real-world environments,where coordinated formation control and obstacle avoidance are essential for executing sophisticated collective tasks.This paper presents a Distributed Formation Control and Obstacle Avoidance(DFCOA)framework for multi-unmanned ground vehicles(UGV).DFCOA integrates a virtual leader structure for global guidance,an improved A^(*)path planning algorithm with an advanced cost function for efficient path planning,and a repulsive-force-based improved vector field histogram star(VFH^(*))technique for collision avoidance.The virtual leader generates a reference trajectory while enabling distributed execution;the improved A^(*)algorithm reduces planning time and number of nodes to determine the shortest path from the starting position to the goal;and the improved VFH^(*)uses 2D LiDAR data with inter-agent repulsive force to simultaneously avoid collision with obstacles and maintain safe inter-vehicle distances.The formation stability of the proposed DFCOA reaches 95.8%and 94.6%in two scenarios,with root mean square(RMS)centroid errors of 0.9516 and 1.0008 m,respectively.Velocity tracking is precise(velocity centroid error RMS of 0.2699 and 0.1700 m/s),and linear velocities closely match the desired 0.3 m/s.Safety metrics showed average collision risks of 0.7773 and 0.5143,with minimum inter-vehicle distances of 0.4702 and 0.8763 m,confirming collision-free navigation of four UGVs.DFCOA outperforms conventional methods in formation stability,path efficiency,and scalability,proving its suitability for decentralized multi-UGV applications.展开更多
This paper presents a hierarchical framework for distributed optimal formation transformation control of unmanned aerial vehicle(UAV)swarms in cluttered environments.The framework decouples the problem into high-level...This paper presents a hierarchical framework for distributed optimal formation transformation control of unmanned aerial vehicle(UAV)swarms in cluttered environments.The framework decouples the problem into high-level assignment and low-level motion planning.First,we introduced the distributed incremental Hungarian-based assignment(DIHBA)algorithm,a communication-efficient method that achieves globally optimal assignments without a central coordinator.For motion planning,a lightweight planner uses a pre-computed library of time-optimal,dynamically feasible trajectories,enabling rapid,safe and formation awareness online selection.Comprehensive simulations demonstrate that framework achieves globally optimal assignments for swarms of up to 200 UAVs with communication costs lower than conventional distributed Hungarian methods,while maintaining superior formation integrity during transformation in cluttered environments.展开更多
Dear Editor,This letter addresses the formation control problem for constrained underactuated autonomous underwater vehicles (AUVs). The feasibility condition of the virtual control law is eliminated by introducing a ...Dear Editor,This letter addresses the formation control problem for constrained underactuated autonomous underwater vehicles (AUVs). The feasibility condition of the virtual control law is eliminated by introducing a nonlinear state dependence function (NSDF) that transforms the state of each AUV in the formation.展开更多
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
Formation control remains a critical challenge in cooperative multi-agent systems,particularly for Unmanned Underwater Vehicles(UUVs).Conventional approaches often suffer from several limitations,including reliance on...Formation control remains a critical challenge in cooperative multi-agent systems,particularly for Unmanned Underwater Vehicles(UUVs).Conventional approaches often suffer from several limitations,including reliance on global information,limited adaptability,high computational complexity,and poor scalability.To address these issues,we propose a novel bio-inspired formation control method for UUV swarms,drawing inspiration from the self-organizing behavior of fish schools.Our method integrates three key components:(1)a coordinated motion strategy without predefined targets that enables individual UUVs to align their movements via simple left or right rotations based solely on local neighbor interactions;(2)a target-directed movement strategy that guides UUVs toward specified regions;and(3)a dispersion control strategy that prevents overcrowding by regulating local spatial distributions.Simulation results confirm that the method achieves robust formation control and efficient area coverage using only local perception.Validation in a 9-UUV simulation environment demonstrates the approach’s flexibility,decentralization,and computational efficiency,making it particularly suitable for large-scale swarms with limited sensing and processing capabilities.展开更多
Formation control in multi-agent systems has become a critical area of interest due to its wide-ranging applications in robotics,autonomous transportation,and surveillance.While various studies have explored distribut...Formation control in multi-agent systems has become a critical area of interest due to its wide-ranging applications in robotics,autonomous transportation,and surveillance.While various studies have explored distributed cooperative control,this review focuses on the theoretical foundations and recent developments in formation control strategies.The paper categorizes and analyzes key formation types,including formation maintenance,group or cluster formation,bipartite formations,event-triggered formations,finite-time convergence,and constrained formations.A significant portion of the review addresses formation control under constrained dynamics,presenting both modelbased and model-free approaches that consider practical limitations such as actuator bounds,communication delays,and nonholonomic constraints.Additionally,the paper discusses emerging trends,including the integration of eventdriven mechanisms and AI-enhanced coordination strategies.Comparative evaluations highlight the trade-offs among various methodologies regarding scalability,robustness,and real-world feasibility.Practical implementations are reviewed across diverse platforms,and the review identifies the current achievements and unresolved challenges in the field.The paper concludes by outlining promising research directions,such as adaptive control for dynamic environments,energy-efficient coordination,and using learning-based control under uncertainty.This review synthesizes the current state of the art and provides a road map for future investigation,making it a valuable reference for researchers and practitioners aiming to advance formation control in multi-agent systems.展开更多
Dear Editor,This letter considers the formation control of multiple mobile robot systems(MMRS)that only relies on the local observation information.A new distributed finite-time observer is proposed for MMRS under dir...Dear Editor,This letter considers the formation control of multiple mobile robot systems(MMRS)that only relies on the local observation information.A new distributed finite-time observer is proposed for MMRS under directed graph to estimate the relative information between each follower robot and the leader robot.Then the formation control problem is transformed into the tracking problem and a finite-time tracking controller is proposed based on the robot model feature.展开更多
In this paper,the distributed optimal formation control problem of heterogeneous Euler–Lagrange multi-agent systems with generic formation constraints and inequality constraints is investigated.Based on the primal–d...In this paper,the distributed optimal formation control problem of heterogeneous Euler–Lagrange multi-agent systems with generic formation constraints and inequality constraints is investigated.Based on the primal–dual dynamics and the adaptive control technique,a distributed optimal formation controller consists of a velocity reference signal generator and a velocity tracking controller is proposed.By using the optimality condition,the relationship between the equilibrium point of the closed-loop system and the optimal solution of the optimization problem is established.Then,by utilizing Lyapunov stability analysis,it is rigorously proved that the optimal formation is reached with the proposed controller.Lastly,simulation examples are provided to substantiate the theoretical results.展开更多
In response to the need for a supportive on-orbit platform for future Mars exploration missions,this paper proposes the design and implementation of an autonomous spacecraft formation flying system near the Martian sy...In response to the need for a supportive on-orbit platform for future Mars exploration missions,this paper proposes the design and implementation of an autonomous spacecraft formation flying system near the Martian synchronous orbit using fuzzy learning-based intelligent control.A detailed analysis of spacecraft relative motion in the Mars environment is conducted,deducing the necessary conditions to reach the Martian synchronous orbit constraints.The modified Clohessy-Wiltshire(C-W)equation with Martian J_(2)(Oblateness index)perturbation is used as a reference to design a fuzzy learning-based intelligent and robust nonlinear control approach,which helps to autonomously track the desired formation configuration and stabilizes it.An introduction to spacecraft propulsion mechanisms is provided to analyze the feasibility of using electrical thrusters for spacecraft formation configuration tracking and stabilization in Martian synchronous orbits.The simulations show the effectiveness of the proposed control system for long-term on-orbit operations and reveal its reliability for designing intelligent deep-space formation flying configurations,such as an autonomous Mars observatory,a Martian telescope,or an interferometer.展开更多
Dear Editor,This letter considers the problem of achieving optimal formation control in multiple vertical take-off and landing(VTOL)unmanned aerial vehicles(UAVs).Specifically,the objective is to derive the vehicles t...Dear Editor,This letter considers the problem of achieving optimal formation control in multiple vertical take-off and landing(VTOL)unmanned aerial vehicles(UAVs).Specifically,the objective is to derive the vehicles to the desired formation shape while minimizing the total cost function.Leveraging the backstepping design,a distributed control strategy is proposed that incorporates a dynamic system for generating a reference trajectory and a trajectory tracking controller for each vehicle.展开更多
An Interval Type-2(IT-2)fuzzy controller design approach is proposed in this research to simultaneously achievemultiple control objectives inNonlinearMulti-Agent Systems(NMASs),including formation,containment,and coll...An Interval Type-2(IT-2)fuzzy controller design approach is proposed in this research to simultaneously achievemultiple control objectives inNonlinearMulti-Agent Systems(NMASs),including formation,containment,and collision avoidance.However,inherent nonlinearities and uncertainties present in practical control systems contribute to the challenge of achieving precise control performance.Based on the IT-2 Takagi-Sugeno Fuzzy Model(T-SFM),the fuzzy control approach can offer a more effective solution for NMASs facing uncertainties.Unlike existing control methods for NMASs,the Formation and Containment(F-and-C)control problem with collision avoidance capability under uncertainties based on the IT-2 T-SFM is discussed for the first time.Moreover,an IT-2 fuzzy tracking control approach is proposed to solve the formation task for leaders in NMASs without requiring communication.This control scheme makes the design process of the IT-2 fuzzy Formation Controller(FC)more straightforward and effective.According to the communication interaction protocol,the IT-2 Containment Controller(CC)design approach is proposed for followers to ensure convergence into the region defined by the leaders.Leveraging the IT-2 T-SFM representation,the analysis methods developed for linear Multi-Agent Systems(MASs)are successfully extended to perform containment analysis without requiring the additional assumptions imposed in existing research.Notably,the IT-2 fuzzy tracking controller can also be applied in collision avoidance situations to track the desired trajectories calculated by the avoidance algorithm under the Artificial Potential Field(APF).Benefiting from the combination of vortex and source APFs,the leaders can properly adjust the system dynamics to prevent potential collision risk.Integrating the fuzzy theory and APFs avoidance algorithm,an IT-2 fuzzy controller design approach is proposed to achieve the F-and-C purposewhile ensuring collision avoidance capability.Finally,amulti-ship simulation is conducted to validate the feasibility and effectiveness of the designed IT-2 fuzzy controller.展开更多
Robust cooperative unmanned aerial vehicle(UAV)formation in complex 3D environments is hampered by reward sparsity and inefficient collaboration.To address this,we propose context-aware relational agent learning(CORAL...Robust cooperative unmanned aerial vehicle(UAV)formation in complex 3D environments is hampered by reward sparsity and inefficient collaboration.To address this,we propose context-aware relational agent learning(CORAL),a novel multi-agent deep reinforcement learning framework.CORAL synergistically integrates two modules:(1)a novelty-based intrinsic reward module to drive efficient exploration and(2)an explicit relational learning module that allows agents to predict peer intentions and enhance coordination.Built on a multi-agent Actor-Critic architecture,CORAL enables agents to balance self-interest with group objectives.Comprehensive evaluations in a high-fidelity simulation show that our method significantly outperforms state-of-theart baselines like multi-agent deep deterministic policy gradient(MADDPG)and monotonic value function factorisation for deep multi-agent reinforcement learning(QMIX)in path planning efficiency,collision avoidance,and scalability.展开更多
In this paper,the flight formation control problem of a group of quadrotor unmanned aerial vehicles（UAVs） with parametric uncertainties and external disturbances is studied.Unitquaternions are used to represent the ...In this paper,the flight formation control problem of a group of quadrotor unmanned aerial vehicles（UAVs） with parametric uncertainties and external disturbances is studied.Unitquaternions are used to represent the attitudes of the quadrotor UAVs.Separating the model into a translational subsystem and a rotational subsystem,an intermediary control input is introduced to track a desired velocity and extract desired orientations.Then considering the internal parametric uncertainties and external disturbances of the quadrotor UAVs,the priori-bounded intermediary adaptive control input is designed for velocity tracking and formation keeping,by which the bounded control thrust and the desired orientation can be extracted.Thereafter,an adaptive control torque input is designed for the rotational subsystem to track the desired orientation.With the proposed control scheme,the desired velocity is tracked and a desired formation shape is built up.Global stability of the closed-loop system is proven via Lyapunov-based stability analysis.Numerical simulation results are presented to illustrate the effectiveness of the proposed control scheme.展开更多
Formation control is a cooperative control concept in which multiple autonomous underwater mobile robots are deployed for a group motion and/or control mission. This paper presents a brief review on various cooperativ...Formation control is a cooperative control concept in which multiple autonomous underwater mobile robots are deployed for a group motion and/or control mission. This paper presents a brief review on various cooperative search and formation control strategies for multiple autonomous underwater vehicles （AUV） based on literature reported till date. Various cooperative and formation control schemes for collecting huge amount of data based on formation regulation control and formation tracking control are discussed. To address the challenge of detecting AUV failure in the fleet, communication issues, collision and obstacle avoidance are also taken into attention. Stability analysis of the feasible formation is also presented. This paper may be intended to serve as a convenient reference for the further research on formation control of multiple underwater mobile robots.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
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
Rare metals including Lithium(Li),Beryllium(Be),Rubidium(Rb),Cesium(Cs),Zirconium(Zr),Hafnium(Hf),Niobium(Nb),Tantalum(Ta),Tungsten(W)and Tin(Sn)are important critical mineral resources.In China,rare metal mineral dep...Rare metals including Lithium(Li),Beryllium(Be),Rubidium(Rb),Cesium(Cs),Zirconium(Zr),Hafnium(Hf),Niobium(Nb),Tantalum(Ta),Tungsten(W)and Tin(Sn)are important critical mineral resources.In China,rare metal mineral deposits are spatially distributed mainly in the Altay and Southern Great Xingán Range regions in the Central Asian orogenic belt;in the Middle Qilian,South Qinling and East Qinling mountains regions in the Qilian-Qinling-Dabie orogenic belt;in the Western Sichuan and Bailongshan-Dahongliutan regions in the Kunlun-Songpan-Garze orogenic belt,and in the Northeastern Jiangxi,Northwestern Jiangxi,and Southern Hunan regions in South China.Major ore-forming epochs include Indosinian(mostly 200-240 Ma,in particular in western China)and the Yanshanian(mostly 120-160 Ma,in particular in South China).In addition,Bayan Obo,Inner Mongolia,northeastern China,with a complex formation history,hosts the largest REE and Nb deposits in China.There are six major rare metal mineral deposit types in China:Highly fractionated granite;Pegmatite;Alkaline granite;Carbonatite and alkaline rock;Volcanic;and Hydrothermal types.Two further types,namely the Leptynite type and Breccia pipe type,have recently been discovered in China,and are represented by the Yushishan Nb-Ta-(Zr-Hf-REE)and the Weilasituo Li-Rb-Sn-W-Zn-Pb deposits.Several most important controlling factors for rare metal mineral deposits are discussed,including geochemical behaviors and sources of the rare metals,highly evolved magmatic fractionation,and structural controls such as the metamorphic core complex setting,with a revised conceptual model for the latter.展开更多
In this paper a stable formation control law that simultaneously ensures collision avoidance has been proposed.It is assumed that the communication graph is undirected and connected.The proposed formation control law ...In this paper a stable formation control law that simultaneously ensures collision avoidance has been proposed.It is assumed that the communication graph is undirected and connected.The proposed formation control law is a combination of the consensus term and the collision avoidance term(CAT).The first order consensus term is derived for the proposed model,while ensuring the Lyapunov stability.The consensus term creates and maintains the desired formation shape,while the CAT avoids the collision.During the collision avoidance,the potential function based CAT makes the agents repel from each other.This unrestricted repelling magnitude cannot ensure the graph connectivity at the time of collision avoidance.Hence we have proposed a formation control law,which ensures this connectivity even during the collision avoidance.This is achieved by the proposed novel adaptive potential function.The potential function adapts itself,with the online tuning of the critical variable associated with it.The tuning has been done based on the lower bound of the critical variable,which is derived from the proposed connectivity property.The efficacy of the proposed scheme has been validated using simulations done based on formations of six and thirty-two agents respectively.展开更多
Consensus tracking control problems for single-integrator dynamics of multi-agent systems with switching topology are investigated. In order to design effective consensus tracking protocols for a more general class of...Consensus tracking control problems for single-integrator dynamics of multi-agent systems with switching topology are investigated. In order to design effective consensus tracking protocols for a more general class of networks, which are aimed at ensuring that the concerned states of agents converge to a constant or time-varying reference state, new consensus tracking protocols with a constant and time-varying reference state are proposed, respectively. Particularly, by contrast with spanning tree, an improved condition of switching interaction topology is presented. And then, convergence analysis of two consensus tracking protocols is provided by Lyapunov stability theory. Moreover, consensus tracking protocol with a time-varying reference state is extended to achieve the fbrmation control. By introducing formation structure set, each agent can gain its individual desired trajectory. Finally, several simulations are worked out to illustrate the effectiveness of theoretical results. The test results show that the states of agents can converge to a desired constant or time-varying reference state. In addition, by selecting appropriate structure set, agents can maintain the expected formation under random switching interaction topologies.展开更多
基金supported by the National Natural Science Foundation of China(62088101,62522307,62273045,U2341213)Beijing Nova Program(20230484481)。
文摘Formation control of multiple spacecraft has attracted extensive research attention.However,achieving reliable performance under sensor failures remains a significant challenge.This paper develops an integrated framework that jointly designs distributed observers and local controllers to ensure robust formation control in the presence of external disturbances and sensor malfunctions.Treating the spacecraft formation as a single interconnected system,each spacecraft constructs a distributed observer that estimates the overall system state by incorporating both its own measurements and the predicted control information shared among the spacecraft.Based on the observer estimates,a local control law is synthesized to maintain the desired formation.Rigorous theoretical analysis and numerical simulations demonstrate that the proposed integrated approach effectively guarantees formation stability and resilience against sensor failures and disturbances.
文摘Researchers are increasingly focused on enabling groups of multiple unmanned vehicles to operate cohesively in complex,real-world environments,where coordinated formation control and obstacle avoidance are essential for executing sophisticated collective tasks.This paper presents a Distributed Formation Control and Obstacle Avoidance(DFCOA)framework for multi-unmanned ground vehicles(UGV).DFCOA integrates a virtual leader structure for global guidance,an improved A^(*)path planning algorithm with an advanced cost function for efficient path planning,and a repulsive-force-based improved vector field histogram star(VFH^(*))technique for collision avoidance.The virtual leader generates a reference trajectory while enabling distributed execution;the improved A^(*)algorithm reduces planning time and number of nodes to determine the shortest path from the starting position to the goal;and the improved VFH^(*)uses 2D LiDAR data with inter-agent repulsive force to simultaneously avoid collision with obstacles and maintain safe inter-vehicle distances.The formation stability of the proposed DFCOA reaches 95.8%and 94.6%in two scenarios,with root mean square(RMS)centroid errors of 0.9516 and 1.0008 m,respectively.Velocity tracking is precise(velocity centroid error RMS of 0.2699 and 0.1700 m/s),and linear velocities closely match the desired 0.3 m/s.Safety metrics showed average collision risks of 0.7773 and 0.5143,with minimum inter-vehicle distances of 0.4702 and 0.8763 m,confirming collision-free navigation of four UGVs.DFCOA outperforms conventional methods in formation stability,path efficiency,and scalability,proving its suitability for decentralized multi-UGV applications.
基金supported in part by the National Key Research and Development Program of China(No.2022YFA1004703)。
文摘This paper presents a hierarchical framework for distributed optimal formation transformation control of unmanned aerial vehicle(UAV)swarms in cluttered environments.The framework decouples the problem into high-level assignment and low-level motion planning.First,we introduced the distributed incremental Hungarian-based assignment(DIHBA)algorithm,a communication-efficient method that achieves globally optimal assignments without a central coordinator.For motion planning,a lightweight planner uses a pre-computed library of time-optimal,dynamically feasible trajectories,enabling rapid,safe and formation awareness online selection.Comprehensive simulations demonstrate that framework achieves globally optimal assignments for swarms of up to 200 UAVs with communication costs lower than conventional distributed Hungarian methods,while maintaining superior formation integrity during transformation in cluttered environments.
基金supported by the National Natural Science Foundation of China(62073094)the Fundamental Research Funds for the Central Universities(3072024GH0404)
文摘Dear Editor,This letter addresses the formation control problem for constrained underactuated autonomous underwater vehicles (AUVs). The feasibility condition of the virtual control law is eliminated by introducing a nonlinear state dependence function (NSDF) that transforms the state of each AUV in the formation.
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supported by The Special Fund for Basic Scientific Research for Liaoning Provincial Governed Universities(2024JBZDZ004)Fishery Central Financial Support Project of Liaoning Province(2023)+5 种基金Liaoning Province Key Research and Development Plan(2023JH26/10200015)Natural Science Foundation of Liaoning Province(2020-KF-12-09)The Liaoning Provincial Education Commission Fund(LJKZ0730,QL202016)Applied Basic Research Project of Science and Technology Commission of Liaoning Province(2022JH2/101300187)Open Fund of Key Laboratory of Environmental Control Aquaculture of Ministry of Education(Dalian Ocean University)(202219)Liaoning Province Science and Technology Plan Joint Program(2024JH2/102600083).
文摘Formation control remains a critical challenge in cooperative multi-agent systems,particularly for Unmanned Underwater Vehicles(UUVs).Conventional approaches often suffer from several limitations,including reliance on global information,limited adaptability,high computational complexity,and poor scalability.To address these issues,we propose a novel bio-inspired formation control method for UUV swarms,drawing inspiration from the self-organizing behavior of fish schools.Our method integrates three key components:(1)a coordinated motion strategy without predefined targets that enables individual UUVs to align their movements via simple left or right rotations based solely on local neighbor interactions;(2)a target-directed movement strategy that guides UUVs toward specified regions;and(3)a dispersion control strategy that prevents overcrowding by regulating local spatial distributions.Simulation results confirm that the method achieves robust formation control and efficient area coverage using only local perception.Validation in a 9-UUV simulation environment demonstrates the approach’s flexibility,decentralization,and computational efficiency,making it particularly suitable for large-scale swarms with limited sensing and processing capabilities.
基金supported in part by the National Natural Science Foundation of China under Grant 6237319in part by the Postgraduate Research and Practice Innovation Program of Jiangsu Province under Grant KYCX230479.
文摘Formation control in multi-agent systems has become a critical area of interest due to its wide-ranging applications in robotics,autonomous transportation,and surveillance.While various studies have explored distributed cooperative control,this review focuses on the theoretical foundations and recent developments in formation control strategies.The paper categorizes and analyzes key formation types,including formation maintenance,group or cluster formation,bipartite formations,event-triggered formations,finite-time convergence,and constrained formations.A significant portion of the review addresses formation control under constrained dynamics,presenting both modelbased and model-free approaches that consider practical limitations such as actuator bounds,communication delays,and nonholonomic constraints.Additionally,the paper discusses emerging trends,including the integration of eventdriven mechanisms and AI-enhanced coordination strategies.Comparative evaluations highlight the trade-offs among various methodologies regarding scalability,robustness,and real-world feasibility.Practical implementations are reviewed across diverse platforms,and the review identifies the current achievements and unresolved challenges in the field.The paper concludes by outlining promising research directions,such as adaptive control for dynamic environments,energy-efficient coordination,and using learning-based control under uncertainty.This review synthesizes the current state of the art and provides a road map for future investigation,making it a valuable reference for researchers and practitioners aiming to advance formation control in multi-agent systems.
基金supported by the National Natural Science Foundation of China(62073113,62003122,62303148)the Fundamental Research Funds for the Central Universities(MCCSE2023A01,JZ2023HGTA0201,JZ2023HGQA0109)the Anhui Provincial Natural Science Foundation(2308085QF204)
文摘Dear Editor,This letter considers the formation control of multiple mobile robot systems(MMRS)that only relies on the local observation information.A new distributed finite-time observer is proposed for MMRS under directed graph to estimate the relative information between each follower robot and the leader robot.Then the formation control problem is transformed into the tracking problem and a finite-time tracking controller is proposed based on the robot model feature.
基金supported in part by the National Key Research and Development Program of China under Grant 2022YFB3303900in part by the National Natural Science Foundation of China under Grants 62103277 and 62025305。
文摘In this paper,the distributed optimal formation control problem of heterogeneous Euler–Lagrange multi-agent systems with generic formation constraints and inequality constraints is investigated.Based on the primal–dual dynamics and the adaptive control technique,a distributed optimal formation controller consists of a velocity reference signal generator and a velocity tracking controller is proposed.By using the optimality condition,the relationship between the equilibrium point of the closed-loop system and the optimal solution of the optimization problem is established.Then,by utilizing Lyapunov stability analysis,it is rigorously proved that the optimal formation is reached with the proposed controller.Lastly,simulation examples are provided to substantiate the theoretical results.
基金supported by the National Laboratory of Space Intelligent Control(No.HTKJ2023KL502007)the Chinese Government Scholarship(CSC)。
文摘In response to the need for a supportive on-orbit platform for future Mars exploration missions,this paper proposes the design and implementation of an autonomous spacecraft formation flying system near the Martian synchronous orbit using fuzzy learning-based intelligent control.A detailed analysis of spacecraft relative motion in the Mars environment is conducted,deducing the necessary conditions to reach the Martian synchronous orbit constraints.The modified Clohessy-Wiltshire(C-W)equation with Martian J_(2)(Oblateness index)perturbation is used as a reference to design a fuzzy learning-based intelligent and robust nonlinear control approach,which helps to autonomously track the desired formation configuration and stabilizes it.An introduction to spacecraft propulsion mechanisms is provided to analyze the feasibility of using electrical thrusters for spacecraft formation configuration tracking and stabilization in Martian synchronous orbits.The simulations show the effectiveness of the proposed control system for long-term on-orbit operations and reveal its reliability for designing intelligent deep-space formation flying configurations,such as an autonomous Mars observatory,a Martian telescope,or an interferometer.
基金supported by the National Natural Science Foundation of China(62003214)Guangdong Basic and Applied Basic Research Foundation(2024A1515012681)+1 种基金the Natural Science Foundation of Shanghai(22ZR1443600)Shanghai Pujiang Programme(23PJD064).
文摘Dear Editor,This letter considers the problem of achieving optimal formation control in multiple vertical take-off and landing(VTOL)unmanned aerial vehicles(UAVs).Specifically,the objective is to derive the vehicles to the desired formation shape while minimizing the total cost function.Leveraging the backstepping design,a distributed control strategy is proposed that incorporates a dynamic system for generating a reference trajectory and a trajectory tracking controller for each vehicle.
基金founded by the National Science and Technology Council of the Republic of China under contract NSTC113-2221-E-019-032.
文摘An Interval Type-2(IT-2)fuzzy controller design approach is proposed in this research to simultaneously achievemultiple control objectives inNonlinearMulti-Agent Systems(NMASs),including formation,containment,and collision avoidance.However,inherent nonlinearities and uncertainties present in practical control systems contribute to the challenge of achieving precise control performance.Based on the IT-2 Takagi-Sugeno Fuzzy Model(T-SFM),the fuzzy control approach can offer a more effective solution for NMASs facing uncertainties.Unlike existing control methods for NMASs,the Formation and Containment(F-and-C)control problem with collision avoidance capability under uncertainties based on the IT-2 T-SFM is discussed for the first time.Moreover,an IT-2 fuzzy tracking control approach is proposed to solve the formation task for leaders in NMASs without requiring communication.This control scheme makes the design process of the IT-2 fuzzy Formation Controller(FC)more straightforward and effective.According to the communication interaction protocol,the IT-2 Containment Controller(CC)design approach is proposed for followers to ensure convergence into the region defined by the leaders.Leveraging the IT-2 T-SFM representation,the analysis methods developed for linear Multi-Agent Systems(MASs)are successfully extended to perform containment analysis without requiring the additional assumptions imposed in existing research.Notably,the IT-2 fuzzy tracking controller can also be applied in collision avoidance situations to track the desired trajectories calculated by the avoidance algorithm under the Artificial Potential Field(APF).Benefiting from the combination of vortex and source APFs,the leaders can properly adjust the system dynamics to prevent potential collision risk.Integrating the fuzzy theory and APFs avoidance algorithm,an IT-2 fuzzy controller design approach is proposed to achieve the F-and-C purposewhile ensuring collision avoidance capability.Finally,amulti-ship simulation is conducted to validate the feasibility and effectiveness of the designed IT-2 fuzzy controller.
基金supported by the STI 2030 Major Projects(No.2022ZD0208804)the National Natural Science Foundation of China(No.62473017)。
文摘Robust cooperative unmanned aerial vehicle(UAV)formation in complex 3D environments is hampered by reward sparsity and inefficient collaboration.To address this,we propose context-aware relational agent learning(CORAL),a novel multi-agent deep reinforcement learning framework.CORAL synergistically integrates two modules:(1)a novelty-based intrinsic reward module to drive efficient exploration and(2)an explicit relational learning module that allows agents to predict peer intentions and enhance coordination.Built on a multi-agent Actor-Critic architecture,CORAL enables agents to balance self-interest with group objectives.Comprehensive evaluations in a high-fidelity simulation show that our method significantly outperforms state-of-theart baselines like multi-agent deep deterministic policy gradient(MADDPG)and monotonic value function factorisation for deep multi-agent reinforcement learning(QMIX)in path planning efficiency,collision avoidance,and scalability.
基金supported by the National Natural Science Foundation of China(No.61374048)
文摘In this paper,the flight formation control problem of a group of quadrotor unmanned aerial vehicles（UAVs） with parametric uncertainties and external disturbances is studied.Unitquaternions are used to represent the attitudes of the quadrotor UAVs.Separating the model into a translational subsystem and a rotational subsystem,an intermediary control input is introduced to track a desired velocity and extract desired orientations.Then considering the internal parametric uncertainties and external disturbances of the quadrotor UAVs,the priori-bounded intermediary adaptive control input is designed for velocity tracking and formation keeping,by which the bounded control thrust and the desired orientation can be extracted.Thereafter,an adaptive control torque input is designed for the rotational subsystem to track the desired orientation.With the proposed control scheme,the desired velocity is tracked and a desired formation shape is built up.Global stability of the closed-loop system is proven via Lyapunov-based stability analysis.Numerical simulation results are presented to illustrate the effectiveness of the proposed control scheme.
文摘Formation control is a cooperative control concept in which multiple autonomous underwater mobile robots are deployed for a group motion and/or control mission. This paper presents a brief review on various cooperative search and formation control strategies for multiple autonomous underwater vehicles （AUV） based on literature reported till date. Various cooperative and formation control schemes for collecting huge amount of data based on formation regulation control and formation tracking control are discussed. To address the challenge of detecting AUV failure in the fleet, communication issues, collision and obstacle avoidance are also taken into attention. Stability analysis of the feasible formation is also presented. This paper may be intended to serve as a convenient reference for the further research on formation control of multiple underwater mobile robots.
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 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financially supported by the National Key R&D Program of China(grant no.2017YFC0602405)the National Natural Science Foundation of China(grant no.42030811)。
文摘Rare metals including Lithium(Li),Beryllium(Be),Rubidium(Rb),Cesium(Cs),Zirconium(Zr),Hafnium(Hf),Niobium(Nb),Tantalum(Ta),Tungsten(W)and Tin(Sn)are important critical mineral resources.In China,rare metal mineral deposits are spatially distributed mainly in the Altay and Southern Great Xingán Range regions in the Central Asian orogenic belt;in the Middle Qilian,South Qinling and East Qinling mountains regions in the Qilian-Qinling-Dabie orogenic belt;in the Western Sichuan and Bailongshan-Dahongliutan regions in the Kunlun-Songpan-Garze orogenic belt,and in the Northeastern Jiangxi,Northwestern Jiangxi,and Southern Hunan regions in South China.Major ore-forming epochs include Indosinian(mostly 200-240 Ma,in particular in western China)and the Yanshanian(mostly 120-160 Ma,in particular in South China).In addition,Bayan Obo,Inner Mongolia,northeastern China,with a complex formation history,hosts the largest REE and Nb deposits in China.There are six major rare metal mineral deposit types in China:Highly fractionated granite;Pegmatite;Alkaline granite;Carbonatite and alkaline rock;Volcanic;and Hydrothermal types.Two further types,namely the Leptynite type and Breccia pipe type,have recently been discovered in China,and are represented by the Yushishan Nb-Ta-(Zr-Hf-REE)and the Weilasituo Li-Rb-Sn-W-Zn-Pb deposits.Several most important controlling factors for rare metal mineral deposits are discussed,including geochemical behaviors and sources of the rare metals,highly evolved magmatic fractionation,and structural controls such as the metamorphic core complex setting,with a revised conceptual model for the latter.
基金supported and funded by the CC&BT Division of the Department of Electronics & Information Technology,Govt,of India(23011/22/2013-R&DIN CC&BT)
文摘In this paper a stable formation control law that simultaneously ensures collision avoidance has been proposed.It is assumed that the communication graph is undirected and connected.The proposed formation control law is a combination of the consensus term and the collision avoidance term(CAT).The first order consensus term is derived for the proposed model,while ensuring the Lyapunov stability.The consensus term creates and maintains the desired formation shape,while the CAT avoids the collision.During the collision avoidance,the potential function based CAT makes the agents repel from each other.This unrestricted repelling magnitude cannot ensure the graph connectivity at the time of collision avoidance.Hence we have proposed a formation control law,which ensures this connectivity even during the collision avoidance.This is achieved by the proposed novel adaptive potential function.The potential function adapts itself,with the online tuning of the critical variable associated with it.The tuning has been done based on the lower bound of the critical variable,which is derived from the proposed connectivity property.The efficacy of the proposed scheme has been validated using simulations done based on formations of six and thirty-two agents respectively.
基金Projects(61075065,60774045) supported by the National Natural Science Foundation of ChinaProject supported by the Graduate Degree Thesis Innovation Foundation of Central South University,China
文摘Consensus tracking control problems for single-integrator dynamics of multi-agent systems with switching topology are investigated. In order to design effective consensus tracking protocols for a more general class of networks, which are aimed at ensuring that the concerned states of agents converge to a constant or time-varying reference state, new consensus tracking protocols with a constant and time-varying reference state are proposed, respectively. Particularly, by contrast with spanning tree, an improved condition of switching interaction topology is presented. And then, convergence analysis of two consensus tracking protocols is provided by Lyapunov stability theory. Moreover, consensus tracking protocol with a time-varying reference state is extended to achieve the fbrmation control. By introducing formation structure set, each agent can gain its individual desired trajectory. Finally, several simulations are worked out to illustrate the effectiveness of theoretical results. The test results show that the states of agents can converge to a desired constant or time-varying reference state. In addition, by selecting appropriate structure set, agents can maintain the expected formation under random switching interaction topologies.
