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
To solve the problems of difficult control law design,poor portability,and poor stability of traditional multi-agent formation obstacle avoidance algorithms,a multi-agent formation obstacle avoidance method based on d...To solve the problems of difficult control law design,poor portability,and poor stability of traditional multi-agent formation obstacle avoidance algorithms,a multi-agent formation obstacle avoidance method based on deep reinforcement learning(DRL)is proposed.This method combines the perception ability of convolutional neural networks(CNNs)with the decision-making ability of reinforcement learning in a general form and realizes direct output control from the visual perception input of the environment to the action through an end-to-end learning method.The multi-agent system(MAS)model of the follow-leader formation method was designed with the wheelbarrow as the control object.An improved deep Q netwrok(DQN)algorithm(we improved its discount factor and learning efficiency and designed a reward value function that considers the distance relationship between the agent and the obstacle and the coordination factor between the multi-agents)was designed to achieve obstacle avoidance and collision avoidance in the process of multi-agent formation into the desired formation.The simulation results show that the proposed method achieves the expected goal of multi-agent formation obstacle avoidance and has stronger portability compared with the traditional algorithm.展开更多
In this paper, we investigate the nonlinear control problem for multi-agent formations with communication delays in noisy environments and in directed interconnection topologies. A stable theory of stochastic delay di...In this paper, we investigate the nonlinear control problem for multi-agent formations with communication delays in noisy environments and in directed interconnection topologies. A stable theory of stochastic delay differential equations is established and then some sufficient conditions are obtained based on this theory, which allow the required formations to be gained at exponentially converging speeds with probability one for time-invariant formations, time-varying formations, and time-varying formations for trajectory tracking under a special"multiple leaders" framework. Some numerical simulations are also given to illustrate the effectiveness of the theoretical results.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
This article investigates the time-varying output group formation tracking control(GFTC)problem for heterogeneous multi-agent systems(HMASs)under switching topologies.The objective is to design a distributed control s...This article investigates the time-varying output group formation tracking control(GFTC)problem for heterogeneous multi-agent systems(HMASs)under switching topologies.The objective is to design a distributed control strategy that enables the outputs of the followers to form the desired sub-formations and track the outputs of the leader in each subgroup.Firstly,novel distributed observers are developed to estimate the states of the leaders under switching topologies.Then,GFTC protocols are designed based on the proposed observers.It is shown that with the distributed protocol,the GFTC problem for HMASs under switching topologies is solved if the average dwell time associated with the switching topologies is larger than a fixed threshold.Finally,an example is provided to illustrate the effectiveness of the proposed control strategy.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
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
The Internet of Unmanned Aerial Vehicles(I-UAVs)is expected to execute latency-sensitive tasks,but limited by co-channel interference and malicious jamming.In the face of unknown prior environmental knowledge,defendin...The Internet of Unmanned Aerial Vehicles(I-UAVs)is expected to execute latency-sensitive tasks,but limited by co-channel interference and malicious jamming.In the face of unknown prior environmental knowledge,defending against jamming and interference through spectrum allocation becomes challenging,especially when each UAV pair makes decisions independently.In this paper,we propose a cooperative multi-agent reinforcement learning(MARL)-based anti-jamming framework for I-UAVs,enabling UAV pairs to learn their own policies cooperatively.Specifically,we first model the problem as a modelfree multi-agent Markov decision process(MAMDP)to maximize the long-term expected system throughput.Then,for improving the exploration of the optimal policy,we resort to optimizing a MARL objective function with a mutual-information(MI)regularizer between states and actions,which can dynamically assign the probability for actions frequently used by the optimal policy.Next,through sharing their current channel selections and local learning experience(their soft Q-values),the UAV pairs can learn their own policies cooperatively relying on only preceding observed information and predicting others’actions.Our simulation results show that for both sweep jamming and Markov jamming patterns,the proposed scheme outperforms the benchmarkers in terms of throughput,convergence and stability for different numbers of jammers,channels and UAV pairs.展开更多
This paper investigates the observer-based prescribed-time time-varying output formation-containment(PT-TV-OFC)control problem for heterogeneous multi-agent systems in which the different agents have different state d...This paper investigates the observer-based prescribed-time time-varying output formation-containment(PT-TV-OFC)control problem for heterogeneous multi-agent systems in which the different agents have different state dimensions.The system comprises one tracking leader,multiple formation leaders,and followers,where two types of leaders are used to generate a reference trajectory for movement and achieve specific formation,respectively.Firstly,a prescribed-time dynamics observer is constructed for the formation leaders to estimate the tracking leader's dynamic model and state.On this basis,a prescribed-time control protocol is designed for the formation leaders to achieve time-varying output formation.Then,a prescribed-time convex hull observer is designed for the followers to estimate information regarding the convex hull formed by the formation leaders.Using the estimated convex hull information,a prescribed-time containment control protocol is designed to ensure the followers converge into the convex hull.Furthermore,using Lyapunov stability theory,the stability of systems is proved in detail,which implies that the heterogeneous multi-agent systems can achieve PT-TV-OFC control.Finally,numerical simulations validate the feasibility of the theoretical results.展开更多
This paper addresses the time-varying formation-containment(FC) problem for nonholonomic multi-agent systems with a desired trajectory constraint, where only the leaders can acquire information about the desired traje...This paper addresses the time-varying formation-containment(FC) problem for nonholonomic multi-agent systems with a desired trajectory constraint, where only the leaders can acquire information about the desired trajectory. Input the fixed time-varying formation template to the leader and start executing, this process also needs to track the desired trajectory, and the follower needs to converge to the convex hull that the leader crosses. Firstly, the dynamic models of nonholonomic systems are linearized to second-order dynamics. Then, based on the desired trajectory and formation template, the FC control protocols are proposed. Sufficient conditions to achieve FC are introduced and an algorithm is proposed to resolve the control parameters by solving an algebraic Riccati equation. The system is demonstrated to achieve FC, with the average position and velocity of the leaders converging asymptotically to the desired trajectory. Finally, the theoretical achievements are verified in simulations by a multi-agent system composed of virtual human individuals.展开更多
Dear Editor,This letter is concerned with the problem of time-varying formation tracking for heterogeneous multi-agent systems(MASs) under directed switching networks. For this purpose, our first step is to present so...Dear Editor,This letter is concerned with the problem of time-varying formation tracking for heterogeneous multi-agent systems(MASs) under directed switching networks. For this purpose, our first step is to present some sufficient conditions for the exponential stability of a particular category of switched systems.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
The multi-satellite electromagnetic formation flight system is nonlinear and strongly coupled,which makes modeling and optimization challenging.To simplify electromagnetic force evaluation and dynamics modeling,we int...The multi-satellite electromagnetic formation flight system is nonlinear and strongly coupled,which makes modeling and optimization challenging.To simplify electromagnetic force evaluation and dynamics modeling,we introduce a reference frame consistent with each satellite body frame,in which the electromagnetic dipoles and electromagnetic forces are represented as two-dimensional vectors.Then,the maneuver time is divided into time intervals,and different satellite sets are activated in each interval,converting the multi-satellite formation reconfiguration problem into an optimal trajectory problem of each two-satellite subsystem.To this end,a token-based dynamic programming method with a switching penalty of active satellite sets is proposed to determine the sequence of satellite sets participating in each time interval,thereby enabling all satellites to reach their desired states.For the two-satellite subsystem with the objectives of minimizing maneuver time and energy consumption,the Gauss pseudo-spectral method is employed to generate the optimal reconfiguration trajectory.Numerical simulations verify the effectiveness of the proposed optimization method.展开更多
This study investigates prescribed-time position tracking control for electromagnetic satellite formations subject to model uncertainties and external disturbances.Using the Clohessy-Wiltshire equations as the relativ...This study investigates prescribed-time position tracking control for electromagnetic satellite formations subject to model uncertainties and external disturbances.Using the Clohessy-Wiltshire equations as the relative motion dynamics model,a prescribed time output feedback control strategy is proposed.A prescribed-time extended state observer is designed to estimate the relative velocity and external disturbances.The disturbance estimates are then used as the feedforward component of the controller.Building on this framework,a novel prescribed-time active disturbance rejection control strategy for position tracking is developed via a backstepping control design.The convergence of the extended state observer and the stability of the closed-loop system are rigorously analyzed using Lyapunov stability theory.Numerical simulations are performed to validate the effectiveness of the proposed controller.展开更多
Cooperative pursuit poses challenges across natural,social,and technical systems,particularly when decentralized,slow-speed pursuers attempt to capture a high-speed evader with limited observation.Most existing contri...Cooperative pursuit poses challenges across natural,social,and technical systems,particularly when decentralized,slow-speed pursuers attempt to capture a high-speed evader with limited observation.Most existing contributions place the focus on the greedy pursuit of the evader,overlooking potential collaborations among pursuers.To tackle this issue,a decisionmaking framework of multi-agent coordinated reciprocity formation pursuit(MACRFP)via deep reinforcement learning is introduced.This framework integrates the actor-critic algorithm with the coordinated reciprocity mechanism to enhance the capability of capturing a faster evader.Initially,a local perception model is created by utilizing a cellular network to simulate limitations caused by obstacles.Next,the formation coalition of pursuit is guided by the Cartesian Oval,enabling dispersed pursuers to create a siege against the faster evader.Furthermore,a coordinated reciprocity model based on the coordination graph and the attention-based graph neural networks is developed,addressing the global coordination problem by estimating a reciprocity coefficient to adjust agents'rewards.Numerical simulations demonstrate the emergence of cooperative behaviors in cooperative besiegement,target tracking,and intelligent interception during the pursuit,indicating that the proposed algorithm enhances the feasibility and effectiveness of capturing a fast-escaping target by integrating coordinated reciprocity and coalition formation.展开更多
Foodborne bacteria produce biofilms and their viable but non-culturable(VBNC)formation,can affect food quality and safety.Studies have shown that these characteristics are regulated by the bacterial quorum sensing(QS)...Foodborne bacteria produce biofilms and their viable but non-culturable(VBNC)formation,can affect food quality and safety.Studies have shown that these characteristics are regulated by the bacterial quorum sensing(QS)system.Quenching the QS system of foodborne bacteria and blocking the expression of the corresponding genes may be an effective way to improve food quality and safety.Therefore,this article reviews the QS systems for foodborne bacteria,the regulatory mechanisms of QS systems in biofilm and VBNC formation and resuscitation,the research progress on quorum sensing inhibitors(QSIs)for Gram-negative and Gram-positive bacteria,and introduces QSIs from various sources.In addition,we have also summarized the current research issues on QS regulation of biofilms and VBNC formation.The systematic study of the QS phenomenon of foodborne bacteria in practical situations,the mechanism of bacterial QS cooperation-cheating,the screening of novel and highly active QSIs,the combination of QSIs and other technologies to improve their bioavailability,and the regulatory network between biofilm and VBNC formation and resuscitation are research directions that need to be paid attention to in the future.展开更多
This paper focuses on the leader-following positive consensus problems of heterogeneous switched multi-agent systems.First,a state-feedback controller with dynamic compensation is introduced to achieve positive consen...This paper focuses on the leader-following positive consensus problems of heterogeneous switched multi-agent systems.First,a state-feedback controller with dynamic compensation is introduced to achieve positive consensus under average dwell time switching.Then sufficient conditions are derived to guarantee the positive consensus.The gain matrices of the control protocol are described using a matrix decomposition approach and the corresponding computational complexity is reduced by resorting to linear programming and co-positive Lyapunov functions.Finally,two numerical examples are provided to illustrate the results obtained.展开更多
Osteoporosis is a systemic skeletal disorder characterized by reduced bone mass,compromised bone microstructure,and an increased risk of fractures,primarily due to excessive osteoclast-mediated bone resorption relativ...Osteoporosis is a systemic skeletal disorder characterized by reduced bone mass,compromised bone microstructure,and an increased risk of fractures,primarily due to excessive osteoclast-mediated bone resorption relative to osteoblast-mediated bone formation.While current anti-osteoporosis drugs,such as bisphosphonates and denosumab,predominantly focus on reducing bone resorption,osteoanabolic approaches are essential for restoring bone microarchitecture and ultimately reducing fracture risk.Traditional Chinese medicines(TCMs)and their active ingredients have long been used in China for osteoporosis prevention and treatment.This review provides a comprehensive evaluation of the effects and molecular mechanisms of 65 natural products across 24 categories on osteoblast-mediated bone formation.These compounds promote bone formation by regulating key transcription factors(RUNX2 and Osterix)and signaling pathways,including WNT/β-catenin,bone morphogenic protein(BMP),mitogen-activated protein kinase(MAPK),phosphoinositide 3-kinase/protein kinase B(PI3K/AKT),oxidative stress,autophagy,and epigenetic regulation.Notably,certain natural products[e.g.,icariin(ICA)]exert their effects through multiple targets and pathways.Many of these natural products have demonstrated significant therapeutic efficacy in animal models,such as ovariectomized(OVX)mice.Our findings suggest that natural products with kidney-tonifying,anti-inflammatory,and antioxidant properties,as well as those inhibiting adipocyte differentiation,may hold promise for osteoporosis treatment.Additionally,we highlight current research gaps and propose future directions,including high-throughput screening and validation in diverse animal models,development of novel bone-targeting delivery systems,and identification of natural compounds targeting osteocytes.展开更多
With the advent of sixth-generation mobile communications(6G),space-air-ground integrated networks have become mainstream.This paper focuses on collaborative scheduling for mobile edge computing(MEC)under a three-tier...With the advent of sixth-generation mobile communications(6G),space-air-ground integrated networks have become mainstream.This paper focuses on collaborative scheduling for mobile edge computing(MEC)under a three-tier heterogeneous architecture composed of mobile devices,unmanned aerial vehicles(UAVs),and macro base stations(BSs).This scenario typically faces fast channel fading,dynamic computational loads,and energy constraints,whereas classical queuing-theoretic or convex-optimization approaches struggle to yield robust solutions in highly dynamic settings.To address this issue,we formulate a multi-agent Markov decision process(MDP)for an air-ground-fused MEC system,unify link selection,bandwidth/power allocation,and task offloading into a continuous action space and propose a joint scheduling strategy that is based on an improved MATD3 algorithm.The improvements include Alternating Layer Normalization(ALN)in the actor to suppress gradient variance,Residual Orthogonalization(RO)in the critic to reduce the correlation between the twin Q-value estimates,and a dynamic-temperature reward to enable adaptive trade-offs during training.On a multi-user,dual-link simulation platform,we conduct ablation and baseline comparisons.The results reveal that the proposed method has better convergence and stability.Compared with MADDPG,TD3,and DSAC,our algorithm achieves more robust performance across key metrics.展开更多
The accumulation and circulation of carbon and hydrogen contribute to the chemical evolution of ice giant planets.Species separation and diamond precipitation have been reported in carbon-hydrogen systems and have bee...The accumulation and circulation of carbon and hydrogen contribute to the chemical evolution of ice giant planets.Species separation and diamond precipitation have been reported in carbon-hydrogen systems and have been verified by static and shock compression experiments.Nevertheless,the dynamic formation processes underlying these phenomena remain insufficiently understood.In combination with a deep learning model,we demonstrate that diamonds form through a three-step process involving dissociation,species separation,and nucleation processes.Under shock conditions of 125 GPa and 4590 K,hydrocarbons decompose to give hydrogen and low-molecular-weight alkanes(CH_(4) and C_(2)H_(6)),which escape from the carbon chains,resulting in C/H species separation.The remaining carbon atoms without C-H bonds accumulate and nucleate to form diamond crystals.The process of diamond growth is associated with a critical nucleus size at which the dynamic energy barrier plays a key role.These dynamic processes of diamond formation provide insight into the establishment of a model for the evolution of ice giant planets.展开更多
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the National Natural Science Foun-dation of China(No.61963006)the Nat-ural Science Foundation of Guangxi Province(Nos.2020GXNSFDA238011,2018GXNSFAA050029,and 2018GXNSFAA294085)。
文摘To solve the problems of difficult control law design,poor portability,and poor stability of traditional multi-agent formation obstacle avoidance algorithms,a multi-agent formation obstacle avoidance method based on deep reinforcement learning(DRL)is proposed.This method combines the perception ability of convolutional neural networks(CNNs)with the decision-making ability of reinforcement learning in a general form and realizes direct output control from the visual perception input of the environment to the action through an end-to-end learning method.The multi-agent system(MAS)model of the follow-leader formation method was designed with the wheelbarrow as the control object.An improved deep Q netwrok(DQN)algorithm(we improved its discount factor and learning efficiency and designed a reward value function that considers the distance relationship between the agent and the obstacle and the coordination factor between the multi-agents)was designed to achieve obstacle avoidance and collision avoidance in the process of multi-agent formation into the desired formation.The simulation results show that the proposed method achieves the expected goal of multi-agent formation obstacle avoidance and has stronger portability compared with the traditional algorithm.
基金Supported by National Natural Science Foundation of China(61403133,61273215,61203148,61072121,61175075)International Postdoctoral Exchange Fellowship Program(20140034)+5 种基金Young Teachers Growth Plan of Hunan University(531107040651)China Postdoctoral Science Foundation(2013M540627)Hunan Provincial Postdoctoral Special Foundation(2013RS4042)Hunan Provincial Postdoctoral Daily Foundation(897202100)Natural Science Foundation of Hunan Province(14JJ3051)Doctoral Fund of Ministry of Education of China(20130161120016)
文摘In this paper, we investigate the nonlinear control problem for multi-agent formations with communication delays in noisy environments and in directed interconnection topologies. A stable theory of stochastic delay differential equations is established and then some sufficient conditions are obtained based on this theory, which allow the required formations to be gained at exponentially converging speeds with probability one for time-invariant formations, time-varying formations, and time-varying formations for trajectory tracking under a special"multiple leaders" framework. Some numerical simulations are also given to illustrate the effectiveness of the theoretical results.
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.
文摘This article investigates the time-varying output group formation tracking control(GFTC)problem for heterogeneous multi-agent systems(HMASs)under switching topologies.The objective is to design a distributed control strategy that enables the outputs of the followers to form the desired sub-formations and track the outputs of the leader in each subgroup.Firstly,novel distributed observers are developed to estimate the states of the leaders under switching topologies.Then,GFTC protocols are designed based on the proposed observers.It is shown that with the distributed protocol,the GFTC problem for HMASs under switching topologies is solved if the average dwell time associated with the switching topologies is larger than a fixed threshold.Finally,an example is provided to illustrate the effectiveness of the proposed control strategy.
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 in part by the National Natural Science Foundation of China under Grants 62001225,62071236,62071234 and U22A2002in part by the Major Science and Technology plan of Hainan Province under Grant ZDKJ2021022+1 种基金in part by the Scientific Research Fund Project of Hainan University under Grant KYQD(ZR)-21008in part by the Key Technologies R&D Program of Jiangsu(Prospective and Key Technologies for Industry)under Grants BE2023022 and BE2023022-2.
文摘The Internet of Unmanned Aerial Vehicles(I-UAVs)is expected to execute latency-sensitive tasks,but limited by co-channel interference and malicious jamming.In the face of unknown prior environmental knowledge,defending against jamming and interference through spectrum allocation becomes challenging,especially when each UAV pair makes decisions independently.In this paper,we propose a cooperative multi-agent reinforcement learning(MARL)-based anti-jamming framework for I-UAVs,enabling UAV pairs to learn their own policies cooperatively.Specifically,we first model the problem as a modelfree multi-agent Markov decision process(MAMDP)to maximize the long-term expected system throughput.Then,for improving the exploration of the optimal policy,we resort to optimizing a MARL objective function with a mutual-information(MI)regularizer between states and actions,which can dynamically assign the probability for actions frequently used by the optimal policy.Next,through sharing their current channel selections and local learning experience(their soft Q-values),the UAV pairs can learn their own policies cooperatively relying on only preceding observed information and predicting others’actions.Our simulation results show that for both sweep jamming and Markov jamming patterns,the proposed scheme outperforms the benchmarkers in terms of throughput,convergence and stability for different numbers of jammers,channels and UAV pairs.
基金supported in part by the National Natural Science Foundation of China(Grant Nos.62473135 and 62173121)。
文摘This paper investigates the observer-based prescribed-time time-varying output formation-containment(PT-TV-OFC)control problem for heterogeneous multi-agent systems in which the different agents have different state dimensions.The system comprises one tracking leader,multiple formation leaders,and followers,where two types of leaders are used to generate a reference trajectory for movement and achieve specific formation,respectively.Firstly,a prescribed-time dynamics observer is constructed for the formation leaders to estimate the tracking leader's dynamic model and state.On this basis,a prescribed-time control protocol is designed for the formation leaders to achieve time-varying output formation.Then,a prescribed-time convex hull observer is designed for the followers to estimate information regarding the convex hull formed by the formation leaders.Using the estimated convex hull information,a prescribed-time containment control protocol is designed to ensure the followers converge into the convex hull.Furthermore,using Lyapunov stability theory,the stability of systems is proved in detail,which implies that the heterogeneous multi-agent systems can achieve PT-TV-OFC control.Finally,numerical simulations validate the feasibility of the theoretical results.
文摘This paper addresses the time-varying formation-containment(FC) problem for nonholonomic multi-agent systems with a desired trajectory constraint, where only the leaders can acquire information about the desired trajectory. Input the fixed time-varying formation template to the leader and start executing, this process also needs to track the desired trajectory, and the follower needs to converge to the convex hull that the leader crosses. Firstly, the dynamic models of nonholonomic systems are linearized to second-order dynamics. Then, based on the desired trajectory and formation template, the FC control protocols are proposed. Sufficient conditions to achieve FC are introduced and an algorithm is proposed to resolve the control parameters by solving an algebraic Riccati equation. The system is demonstrated to achieve FC, with the average position and velocity of the leaders converging asymptotically to the desired trajectory. Finally, the theoretical achievements are verified in simulations by a multi-agent system composed of virtual human individuals.
基金supported in part by the National Natural Science Foundation of China(62273255,62350003,62088101)the Shanghai Science and Technology Cooperation Project(22510712000,21550760900)+1 种基金the Shanghai Municipal Science and Technology Major Project(2021SHZDZX0100)the Fundamental Research Funds for the Central Universities
文摘Dear Editor,This letter is concerned with the problem of time-varying formation tracking for heterogeneous multi-agent systems(MASs) under directed switching networks. For this purpose, our first step is to present some sufficient conditions for the exponential stability of a particular category of switched systems.
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.
文摘The multi-satellite electromagnetic formation flight system is nonlinear and strongly coupled,which makes modeling and optimization challenging.To simplify electromagnetic force evaluation and dynamics modeling,we introduce a reference frame consistent with each satellite body frame,in which the electromagnetic dipoles and electromagnetic forces are represented as two-dimensional vectors.Then,the maneuver time is divided into time intervals,and different satellite sets are activated in each interval,converting the multi-satellite formation reconfiguration problem into an optimal trajectory problem of each two-satellite subsystem.To this end,a token-based dynamic programming method with a switching penalty of active satellite sets is proposed to determine the sequence of satellite sets participating in each time interval,thereby enabling all satellites to reach their desired states.For the two-satellite subsystem with the objectives of minimizing maneuver time and energy consumption,the Gauss pseudo-spectral method is employed to generate the optimal reconfiguration trajectory.Numerical simulations verify the effectiveness of the proposed optimization method.
文摘This study investigates prescribed-time position tracking control for electromagnetic satellite formations subject to model uncertainties and external disturbances.Using the Clohessy-Wiltshire equations as the relative motion dynamics model,a prescribed time output feedback control strategy is proposed.A prescribed-time extended state observer is designed to estimate the relative velocity and external disturbances.The disturbance estimates are then used as the feedforward component of the controller.Building on this framework,a novel prescribed-time active disturbance rejection control strategy for position tracking is developed via a backstepping control design.The convergence of the extended state observer and the stability of the closed-loop system are rigorously analyzed using Lyapunov stability theory.Numerical simulations are performed to validate the effectiveness of the proposed controller.
基金supported by the National Natural Science Foundation of China(72371052,71871042)。
文摘Cooperative pursuit poses challenges across natural,social,and technical systems,particularly when decentralized,slow-speed pursuers attempt to capture a high-speed evader with limited observation.Most existing contributions place the focus on the greedy pursuit of the evader,overlooking potential collaborations among pursuers.To tackle this issue,a decisionmaking framework of multi-agent coordinated reciprocity formation pursuit(MACRFP)via deep reinforcement learning is introduced.This framework integrates the actor-critic algorithm with the coordinated reciprocity mechanism to enhance the capability of capturing a faster evader.Initially,a local perception model is created by utilizing a cellular network to simulate limitations caused by obstacles.Next,the formation coalition of pursuit is guided by the Cartesian Oval,enabling dispersed pursuers to create a siege against the faster evader.Furthermore,a coordinated reciprocity model based on the coordination graph and the attention-based graph neural networks is developed,addressing the global coordination problem by estimating a reciprocity coefficient to adjust agents'rewards.Numerical simulations demonstrate the emergence of cooperative behaviors in cooperative besiegement,target tracking,and intelligent interception during the pursuit,indicating that the proposed algorithm enhances the feasibility and effectiveness of capturing a fast-escaping target by integrating coordinated reciprocity and coalition formation.
基金financially supported by the National Natural Science Foundation of China(32202191)and(32272279)the Key R&D Project of Shandong Province(2023CXPT007 and 2024CXPT014)the Key R&D Project of Qingdao Science and Technology Plan(24-2-3-4-zyyd-jch).
文摘Foodborne bacteria produce biofilms and their viable but non-culturable(VBNC)formation,can affect food quality and safety.Studies have shown that these characteristics are regulated by the bacterial quorum sensing(QS)system.Quenching the QS system of foodborne bacteria and blocking the expression of the corresponding genes may be an effective way to improve food quality and safety.Therefore,this article reviews the QS systems for foodborne bacteria,the regulatory mechanisms of QS systems in biofilm and VBNC formation and resuscitation,the research progress on quorum sensing inhibitors(QSIs)for Gram-negative and Gram-positive bacteria,and introduces QSIs from various sources.In addition,we have also summarized the current research issues on QS regulation of biofilms and VBNC formation.The systematic study of the QS phenomenon of foodborne bacteria in practical situations,the mechanism of bacterial QS cooperation-cheating,the screening of novel and highly active QSIs,the combination of QSIs and other technologies to improve their bioavailability,and the regulatory network between biofilm and VBNC formation and resuscitation are research directions that need to be paid attention to in the future.
基金supported by the National Natural Science Foundation of China(62463007,62463005)the Natural Science Foundation of Hainan Province(625RC710,625MS047)+1 种基金the System Control and Information Processing Education Ministry Key Laboratory Open Funding,China(Scip20240119)the Science Research Funding of Hainan University,China(KYQD(ZR)22180,KYQD(ZR)23180).
文摘This paper focuses on the leader-following positive consensus problems of heterogeneous switched multi-agent systems.First,a state-feedback controller with dynamic compensation is introduced to achieve positive consensus under average dwell time switching.Then sufficient conditions are derived to guarantee the positive consensus.The gain matrices of the control protocol are described using a matrix decomposition approach and the corresponding computational complexity is reduced by resorting to linear programming and co-positive Lyapunov functions.Finally,two numerical examples are provided to illustrate the results obtained.
基金supported by the National Natural Science Foundation of China(No.31800059)。
文摘Osteoporosis is a systemic skeletal disorder characterized by reduced bone mass,compromised bone microstructure,and an increased risk of fractures,primarily due to excessive osteoclast-mediated bone resorption relative to osteoblast-mediated bone formation.While current anti-osteoporosis drugs,such as bisphosphonates and denosumab,predominantly focus on reducing bone resorption,osteoanabolic approaches are essential for restoring bone microarchitecture and ultimately reducing fracture risk.Traditional Chinese medicines(TCMs)and their active ingredients have long been used in China for osteoporosis prevention and treatment.This review provides a comprehensive evaluation of the effects and molecular mechanisms of 65 natural products across 24 categories on osteoblast-mediated bone formation.These compounds promote bone formation by regulating key transcription factors(RUNX2 and Osterix)and signaling pathways,including WNT/β-catenin,bone morphogenic protein(BMP),mitogen-activated protein kinase(MAPK),phosphoinositide 3-kinase/protein kinase B(PI3K/AKT),oxidative stress,autophagy,and epigenetic regulation.Notably,certain natural products[e.g.,icariin(ICA)]exert their effects through multiple targets and pathways.Many of these natural products have demonstrated significant therapeutic efficacy in animal models,such as ovariectomized(OVX)mice.Our findings suggest that natural products with kidney-tonifying,anti-inflammatory,and antioxidant properties,as well as those inhibiting adipocyte differentiation,may hold promise for osteoporosis treatment.Additionally,we highlight current research gaps and propose future directions,including high-throughput screening and validation in diverse animal models,development of novel bone-targeting delivery systems,and identification of natural compounds targeting osteocytes.
文摘With the advent of sixth-generation mobile communications(6G),space-air-ground integrated networks have become mainstream.This paper focuses on collaborative scheduling for mobile edge computing(MEC)under a three-tier heterogeneous architecture composed of mobile devices,unmanned aerial vehicles(UAVs),and macro base stations(BSs).This scenario typically faces fast channel fading,dynamic computational loads,and energy constraints,whereas classical queuing-theoretic or convex-optimization approaches struggle to yield robust solutions in highly dynamic settings.To address this issue,we formulate a multi-agent Markov decision process(MDP)for an air-ground-fused MEC system,unify link selection,bandwidth/power allocation,and task offloading into a continuous action space and propose a joint scheduling strategy that is based on an improved MATD3 algorithm.The improvements include Alternating Layer Normalization(ALN)in the actor to suppress gradient variance,Residual Orthogonalization(RO)in the critic to reduce the correlation between the twin Q-value estimates,and a dynamic-temperature reward to enable adaptive trade-offs during training.On a multi-user,dual-link simulation platform,we conduct ablation and baseline comparisons.The results reveal that the proposed method has better convergence and stability.Compared with MADDPG,TD3,and DSAC,our algorithm achieves more robust performance across key metrics.
基金supported by the National Natural Science Foundation of China(Grant Nos.12534013,12047561,and 12104507)the Science and Technology Innovation Program of Hunan Province(Grant Nos.2025ZYJ001 and 2021RC4026)the National University of Defense Technology Research Fund Project.
文摘The accumulation and circulation of carbon and hydrogen contribute to the chemical evolution of ice giant planets.Species separation and diamond precipitation have been reported in carbon-hydrogen systems and have been verified by static and shock compression experiments.Nevertheless,the dynamic formation processes underlying these phenomena remain insufficiently understood.In combination with a deep learning model,we demonstrate that diamonds form through a three-step process involving dissociation,species separation,and nucleation processes.Under shock conditions of 125 GPa and 4590 K,hydrocarbons decompose to give hydrogen and low-molecular-weight alkanes(CH_(4) and C_(2)H_(6)),which escape from the carbon chains,resulting in C/H species separation.The remaining carbon atoms without C-H bonds accumulate and nucleate to form diamond crystals.The process of diamond growth is associated with a critical nucleus size at which the dynamic energy barrier plays a key role.These dynamic processes of diamond formation provide insight into the establishment of a model for the evolution of ice giant planets.
