In this paper,a new distributed consensus tracking protocol incorporating local disturbance rejection is devised for a multi-agent system with heterogeneous dynamic uncertainties and disturbances over a directed graph...In this paper,a new distributed consensus tracking protocol incorporating local disturbance rejection is devised for a multi-agent system with heterogeneous dynamic uncertainties and disturbances over a directed graph.It is of two-degree-of-freedom nature.Specifically,a robust distributed controller is designed for consensus tracking,while a local disturbance estimator is designed for each agent without requiring the input channel information of disturbances.The condition for asymptotic disturbance rejection is derived.Moreover,even when the disturbance model is not exactly known,the developed method also provides good disturbance-rejection performance.Then,a robust stabilization condition with less conservativeness is derived for the whole multi-agent system.Further,a design algorithm is given.Finally,comparisons with the conventional one-degree-of-freedombased distributed disturbance-rejection method for mismatched disturbances and the distributed extended-state observer for matched disturbances validate the developed method.展开更多
In this paper,the event-triggered consensus control problem for nonlinear uncertain multi-agent systems subject to unknown parameters and external disturbances is considered.The dynamics of subsystems are second-order...In this paper,the event-triggered consensus control problem for nonlinear uncertain multi-agent systems subject to unknown parameters and external disturbances is considered.The dynamics of subsystems are second-order with similar structures,and the nodes are connected by undirected graphs.The event-triggered mechanisms are not only utilized in the transmission of information from the controllers to the actuators,and from the sensors to the controllers within each agent,but also in the communication between agents.Based on the adaptive backstepping method,extra estimators are introduced to handle the unknown parameters,and the measurement errors that occur during the event-triggered communication are well handled by designing compensating terms for the control signals.The presented distributed event-triggered adaptive control laws can guarantee the boundness of the consensus tracking errors and the Zeno behavior is avoided.Meanwhile,the update frequency of the controllers and the load of communication burden are vastly reduced.The obtained control protocol is further applied to a multi-input multi-output second-order nonlinear multi-agent system,and the simulation results show the effectiveness and advantages of our proposed method.展开更多
In this paper, the robust analysis and design of leader-following output regulation for multi-agent systems described by general linear models is given in presence of timevarying delay and model uncertainty. To this a...In this paper, the robust analysis and design of leader-following output regulation for multi-agent systems described by general linear models is given in presence of timevarying delay and model uncertainty. To this aim, a new regulation protocol for the closed-loop multi-agent system under a directed graph is proposed. An important specification of the proposed protocol is to guarantee the leader-following output regulation for uncertain multi-agent systems with both stable and unstable agents. Since many signals can be approximated by a combination of the stationary and ramp signals, the presented results work for adequate variety of the leaders. The analysis and design conditions are presented in terms of certain matrix inequalities. The method proposed can be used for both stationary and ramp leaders. Simulation results are presented to show the effectiveness of the proposed method.展开更多
Dear Editor,An adaptive consensus control algorithm for uncertain multi-agent systems(MAS),capable of guaranteeing unified prescribed performance,is presented in this letter.Unlike many existing prescribed performance...Dear Editor,An adaptive consensus control algorithm for uncertain multi-agent systems(MAS),capable of guaranteeing unified prescribed performance,is presented in this letter.Unlike many existing prescribed performance related works,the developed control exhibits some features.Firstly,a distributed prescribed time observer is introduced so that not only each follower is able to estimate the leader’s signal within a predetermined time,but also the control design for each agent is independent with its neighbors.展开更多
This paper delves into the problem of optimal placement conditions for a group of agents collaboratively localizing a target using range-only or bearing-only measurements.The challenge in this study stems from the unc...This paper delves into the problem of optimal placement conditions for a group of agents collaboratively localizing a target using range-only or bearing-only measurements.The challenge in this study stems from the uncertainty associated with the positions of the agents,which may experience drift or disturbances during the target localization process.Initially,we derive the Cramer-Rao lower bound(CRLB)of the target position as the primary analytical metric.Subsequently,we establish the necessary and sufficient conditions for the optimal placement of agents.Based on these conditions,we analyze the maximal allowable agent position error for an expected mean squared error(MSE),providing valuable guidance for the selection of agent positioning sensors.The analytical findings are further validated through simulation experiments.展开更多
Containment control of first-order multi-agent systems with uncertain topologies and communication timedelays is studied. Suppose system topologies are dynamically changed, a containment control algorithm with time-va...Containment control of first-order multi-agent systems with uncertain topologies and communication timedelays is studied. Suppose system topologies are dynamically changed, a containment control algorithm with time-varying delays is presented. The stability of the control algorithm is studied under the assumption that communication topologies are jointly-connected, and constraint condition of distributed containment control for delayed multi-agent systems is derived with the aid of Lyapunov–Krasovskii function. Simulation results are provided to prove the correctness and effectiveness of the conclusion.展开更多
The objective of this paper is to investigate the consensus of the multi-agent systems w/th nonlinear coupling function and external disturbances. The disturbance includes two parts, one part is supposed to be generat...The objective of this paper is to investigate the consensus of the multi-agent systems w/th nonlinear coupling function and external disturbances. The disturbance includes two parts, one part is supposed to be generated by an exogenous system, which is not required to be neutrally stable as in the output regulation theory, the other part is the modeling uncertainty in the exogenous disturbance system. A novel composite disturbance observer based control （DOBC） and H∞ control scheme is presented so that the disturbance with the exogenous system can be estimated and compensated and the consensus of the multi-agent systems with fixed and switching graph can be reached by using Hoo control law. Simulations demonstrate the advantages of the proposed DOBC and H∞ control scheme.展开更多
In this paper,the bipartite consensus problem is studied for a class of uncertain high-order nonlinear multi-agent systems.A signed digraph is presented to describe the collaborative and competitive interactions among...In this paper,the bipartite consensus problem is studied for a class of uncertain high-order nonlinear multi-agent systems.A signed digraph is presented to describe the collaborative and competitive interactions among agents.For each agent with lower triangular structure,a time-varying gain compensator is first designed by relative output information of neighboring agents.Subsequently,a distributed controller with dynamic event-triggered mechanism is proposed to drive the bipartite consensus error to zero.It is worth noting that an internal dynamic variable is introduced in triggering function,which plays an essential role in excluding the Zeno behavior and reducing energy consumption.Furthermore,the dynamic event-triggered control protocol is developed for upper triangular multi-agent systems to realize the bipartite consensus without Zeno behavior.Finally,simulation examples are provided to illustrate the effectiveness of the presented results.展开更多
In this paper, the leader-following tracking problem of fractional-order multi-agent systems is addressed. The dynamics of each agent may be heterogeneous and has unknown nonlinearities. By assumptions that the intera...In this paper, the leader-following tracking problem of fractional-order multi-agent systems is addressed. The dynamics of each agent may be heterogeneous and has unknown nonlinearities. By assumptions that the interaction topology is undirected and connected and the unknown nonlinear uncertain dynamics can be parameterized by a neural network, an adaptive learning law is proposed to deal with unknown nonlinear dynamics, based on which a kind of cooperative tracking protocols are constructed. The feedback gain matrix is obtained to solve an algebraic Riccati equation. To construct the fully distributed cooperative tracking protocols, the adaptive law is also adopted to adjust the coupling weight. With the developed control laws,we can prove that all signals in the closed-loop systems are guaranteed to be uniformly ultimately bounded. Finally, a simple simulation example is provided to illustrate the established result.展开更多
In this paper, we consider the distributed adaptive fault-tolerant output regulation problem for heterogeneous multiagent systems with matched system uncertainties and mismatched coupling uncertainties among subsystem...In this paper, we consider the distributed adaptive fault-tolerant output regulation problem for heterogeneous multiagent systems with matched system uncertainties and mismatched coupling uncertainties among subsystems under the influence of actuator faults. First, distributed finite-time observers are proposed for all subsystems to observe the state of the exosystem. Then, a novel fault-tolerant controller is designed to compensate for the influence of matched system uncertainties and actuator faults. By using the linear matrix inequality technique, a sufficient condition is provided to guarantee the solvability of the considered problem in the presence of mismatched coupling uncertainties. Moreover, it is shown that the system in closed-loop with the developed controller can achieve output regulation by using the Lyapunov stability theory and cyclic-small-gain theory.Finally, a numerical example is given to illustrate the effectiveness of the obtained result.展开更多
Cooperative multi-agent reinforcement learning(MARL)is a key technology for enabling cooperation in complex multi-agent systems.It has achieved remarkable progress in areas such as gaming,autonomous driving,and multi-...Cooperative multi-agent reinforcement learning(MARL)is a key technology for enabling cooperation in complex multi-agent systems.It has achieved remarkable progress in areas such as gaming,autonomous driving,and multi-robot control.Empowering cooperative MARL with multi-task decision-making capabilities is expected to further broaden its application scope.In multi-task scenarios,cooperative MARL algorithms need to address 3 types of multi-task problems:reward-related multi-task,arising from different reward functions;multi-domain multi-task,caused by differences in state and action spaces,state transition functions;and scalability-related multi-task,resulting from the dynamic variation in the number of agents.Most existing studies focus on scalability-related multitask problems.However,with the increasing integration between large language models(LLMs)and multi-agent systems,a growing number of LLM-based multi-agent systems have emerged,enabling more complex multi-task cooperation.This paper provides a comprehensive review of the latest advances in this field.By combining multi-task reinforcement learning with cooperative MARL,we categorize and analyze the 3 major types of multi-task problems under multi-agent settings,offering more fine-grained classifications and summarizing key insights for each.In addition,we summarize commonly used benchmarks and discuss future directions of research in this area,which hold promise for further enhancing the multi-task cooperation capabilities of multi-agent systems and expanding their practical applications in the real world.展开更多
This paper addresses the consensus problem of nonlinear multi-agent systems subject to external disturbances and uncertainties under denial-ofservice(DoS)attacks.Firstly,an observer-based state feedback control method...This paper addresses the consensus problem of nonlinear multi-agent systems subject to external disturbances and uncertainties under denial-ofservice(DoS)attacks.Firstly,an observer-based state feedback control method is employed to achieve secure control by estimating the system's state in real time.Secondly,by combining a memory-based adaptive eventtriggered mechanism with neural networks,the paper aims to approximate the nonlinear terms in the networked system and efficiently conserve system resources.Finally,based on a two-degree-of-freedom model of a vehicle affected by crosswinds,this paper constructs a multi-unmanned ground vehicle(Multi-UGV)system to validate the effectiveness of the proposed method.Simulation results show that the proposed control strategy can effectively handle external disturbances such as crosswinds in practical applications,ensuring the stability and reliable operation of the Multi-UGV system.展开更多
In this paper, we study the leader-following rendezvous and flocking problems for a class of second-order nonlinear multi- agent systems, which contain both external disturbances and plant uncertainties. What differs ...In this paper, we study the leader-following rendezvous and flocking problems for a class of second-order nonlinear multi- agent systems, which contain both external disturbances and plant uncertainties. What differs our problems from the conventional leader-following consensus problem is that we need to preserve the connectivity of the communication graph instead of assuming the connectivity of the communication graph. By integrating the adaptive control technique, the distributed observer method and the potential function method, the two problems are both solved. Finally, we apply our results to a group of van der Pol oscillators.展开更多
This paper studies the leader-following consensus problem for a class of second-order nonlinear multi-agent systems subject to linearly parameterized uncertainty and disturbance. The problem is solved by integrating t...This paper studies the leader-following consensus problem for a class of second-order nonlinear multi-agent systems subject to linearly parameterized uncertainty and disturbance. The problem is solved by integrating the adaptive control technique and the adaptive distributed observer method. The design procedure is illustrated by an example with a group of Van der Pol oscillators as the followers and a harmonic system as the leader.展开更多
In this paper,the distributed fuzzy fault-tolerant tracking consensus problem of leader-follower multi-agent systems(MASs)is studied.The objective system includes actuator faults,mismatched parameter uncertainties,non...In this paper,the distributed fuzzy fault-tolerant tracking consensus problem of leader-follower multi-agent systems(MASs)is studied.The objective system includes actuator faults,mismatched parameter uncertainties,nonlinear functions,and exogenous disturbances under switching communication topologies.To solve this problem,a distributed fuzzy fault-tolerant controller is proposed for each follower by adaptive mechanisms to track the state of the leader.Furthermore,the fuzzy logic system is utilized to approximate the unknown nonlinear dynamics.An error estimator is introduced between the mismatched parameter matrix and the input matrix.Then,a selective adaptive law with relative state information is adopted and applied.When calculating the Lyapunov function’s derivative,the coupling terms related to consensus error and mismatched parameter uncertainties can be eliminated.Finally,a numerical simulation is given to validate the effectiveness of the proposed protocol.展开更多
This paper is concerned with distributed containment maneuvering of second-order Multi-Input Multi-Output(MIMO)multi-agent systems with non-periodic communication and actuation.The agent is subject to unmatched nonlin...This paper is concerned with distributed containment maneuvering of second-order Multi-Input Multi-Output(MIMO)multi-agent systems with non-periodic communication and actuation.The agent is subject to unmatched nonlinear dynamics and external disturbances.Event-triggered containment maneuvering control methods is developed based on a modular design.Specifically,an estimator module is constructed based on neural networks and the nonperiodic obtained follower information through event-triggered communication.Next,a controller module is designed by using the identified information from the estimator module and a third-order linear tracking differentiator.An event-triggered mechanism is introduced for updating the actuator.Then,a path update law is designed based on the non-periodic leader information through event-triggered communication.The closed-loop system cascaded by the estimation subsystem and control subsystem is proved to be input-to-state stable,and Zeno behavior is excluded in the control process.The proposed method is capable of reducing the consumption of communication and actuation.A simulation example is provided to substantiate the effectiveness of the proposed event-triggered control method for distributed containment maneuvering of second-order MIMO multi-agent systems.展开更多
We propose a new approach to discuss the consensus problem of multi-agent systems with time-varying delayed control inputs, switching topologies, and stochastic cyber-attacks under hybrid-triggered mechanism.A Bernoul...We propose a new approach to discuss the consensus problem of multi-agent systems with time-varying delayed control inputs, switching topologies, and stochastic cyber-attacks under hybrid-triggered mechanism.A Bernoulli variable is used to describe the hybrid-triggered scheme, which is introduced to alleviate the burden of the network.The mathematical model of the closed-loop control system is established by taking the influences of time-varying delayed control inputs,switching topologies, and stochastic cyber-attacks into account under the hybrid-triggered scheme.A theorem as the main result is given to make the system consistent based on the theory of Lyapunov stability and linear matrix inequality.Markov jumps with uncertain rates of transitions are applied to describe the switch of topologies.Finally, a simulation example demonstrates the feasibility of the theory in this paper.展开更多
This paper investigates the challenges associated with Unmanned Aerial Vehicle (UAV) collaborative search and target tracking in dynamic and unknown environments characterized by limited field of view. The primary obj...This paper investigates the challenges associated with Unmanned Aerial Vehicle (UAV) collaborative search and target tracking in dynamic and unknown environments characterized by limited field of view. The primary objective is to explore the unknown environments to locate and track targets effectively. To address this problem, we propose a novel Multi-Agent Reinforcement Learning (MARL) method based on Graph Neural Network (GNN). Firstly, a method is introduced for encoding continuous-space multi-UAV problem data into spatial graphs which establish essential relationships among agents, obstacles, and targets. Secondly, a Graph AttenTion network (GAT) model is presented, which focuses exclusively on adjacent nodes, learns attention weights adaptively and allows agents to better process information in dynamic environments. Reward functions are specifically designed to tackle exploration challenges in environments with sparse rewards. By introducing a framework that integrates centralized training and distributed execution, the advancement of models is facilitated. Simulation results show that the proposed method outperforms the existing MARL method in search rate and tracking performance with less collisions. The experiments show that the proposed method can be extended to applications with a larger number of agents, which provides a potential solution to the challenging problem of multi-UAV autonomous tracking in dynamic unknown environments.展开更多
基金supported by the National Natural Science Foundation of China(62003010,61873006,61673053)the Beijing Postdoctoral Research Foundation(Q6041001202001)+1 种基金the Postdoctoral Research Foundation of Chaoyang District(Q1041001202101)the National Key Research and Development Project(2018YFC1602704,2018YFB1702704)。
文摘In this paper,a new distributed consensus tracking protocol incorporating local disturbance rejection is devised for a multi-agent system with heterogeneous dynamic uncertainties and disturbances over a directed graph.It is of two-degree-of-freedom nature.Specifically,a robust distributed controller is designed for consensus tracking,while a local disturbance estimator is designed for each agent without requiring the input channel information of disturbances.The condition for asymptotic disturbance rejection is derived.Moreover,even when the disturbance model is not exactly known,the developed method also provides good disturbance-rejection performance.Then,a robust stabilization condition with less conservativeness is derived for the whole multi-agent system.Further,a design algorithm is given.Finally,comparisons with the conventional one-degree-of-freedombased distributed disturbance-rejection method for mismatched disturbances and the distributed extended-state observer for matched disturbances validate the developed method.
基金supported by National Key R&D Program of China(No.2018YFA0703800)Science Fund for Creative Research Group of the National Natural Science Foundation of China(No.61621002)。
文摘In this paper,the event-triggered consensus control problem for nonlinear uncertain multi-agent systems subject to unknown parameters and external disturbances is considered.The dynamics of subsystems are second-order with similar structures,and the nodes are connected by undirected graphs.The event-triggered mechanisms are not only utilized in the transmission of information from the controllers to the actuators,and from the sensors to the controllers within each agent,but also in the communication between agents.Based on the adaptive backstepping method,extra estimators are introduced to handle the unknown parameters,and the measurement errors that occur during the event-triggered communication are well handled by designing compensating terms for the control signals.The presented distributed event-triggered adaptive control laws can guarantee the boundness of the consensus tracking errors and the Zeno behavior is avoided.Meanwhile,the update frequency of the controllers and the load of communication burden are vastly reduced.The obtained control protocol is further applied to a multi-input multi-output second-order nonlinear multi-agent system,and the simulation results show the effectiveness and advantages of our proposed method.
基金supported by the Natural Science and Engineering Research Council(NSERC)of Canada(RES0001828)
文摘In this paper, the robust analysis and design of leader-following output regulation for multi-agent systems described by general linear models is given in presence of timevarying delay and model uncertainty. To this aim, a new regulation protocol for the closed-loop multi-agent system under a directed graph is proposed. An important specification of the proposed protocol is to guarantee the leader-following output regulation for uncertain multi-agent systems with both stable and unstable agents. Since many signals can be approximated by a combination of the stationary and ramp signals, the presented results work for adequate variety of the leaders. The analysis and design conditions are presented in terms of certain matrix inequalities. The method proposed can be used for both stationary and ramp leaders. Simulation results are presented to show the effectiveness of the proposed method.
基金supported in part by the National Key Research and Development Program of China(2022YFB4701400/4701401)the National Natural Science Foundation of China(61991400,61991403,62250710167,61860206008,61933012,62273064)+1 种基金the Chongqing Outstanding Young Talents Support Program(cstc2024ycjh-bgzxm0085)CAAI-Huawei MindSpore Open Fund。
文摘Dear Editor,An adaptive consensus control algorithm for uncertain multi-agent systems(MAS),capable of guaranteeing unified prescribed performance,is presented in this letter.Unlike many existing prescribed performance related works,the developed control exhibits some features.Firstly,a distributed prescribed time observer is introduced so that not only each follower is able to estimate the leader’s signal within a predetermined time,but also the control design for each agent is independent with its neighbors.
文摘This paper delves into the problem of optimal placement conditions for a group of agents collaboratively localizing a target using range-only or bearing-only measurements.The challenge in this study stems from the uncertainty associated with the positions of the agents,which may experience drift or disturbances during the target localization process.Initially,we derive the Cramer-Rao lower bound(CRLB)of the target position as the primary analytical metric.Subsequently,we establish the necessary and sufficient conditions for the optimal placement of agents.Based on these conditions,we analyze the maximal allowable agent position error for an expected mean squared error(MSE),providing valuable guidance for the selection of agent positioning sensors.The analytical findings are further validated through simulation experiments.
基金Supported by National Natural Science Foundation of China （61074032, 61473182, 61104089）, National High Technology Research and Development Program of China （863 Program） （2011AA040103-7）, Project of Science and Technology Commission of Shanghai Municipality （10JC1405000, 11ZR1413100,14JC1402200）, and Shanghai Rising-Star Program （13QA1401600）
基金Supported by the National Natural Science Foundation of China under Grant Nos.61273152,61304052,51407088the Science Foundation of Education Office of Shandong Province of China under Grant Nos.ZR2011FM07,BS2015DX018
文摘Containment control of first-order multi-agent systems with uncertain topologies and communication timedelays is studied. Suppose system topologies are dynamically changed, a containment control algorithm with time-varying delays is presented. The stability of the control algorithm is studied under the assumption that communication topologies are jointly-connected, and constraint condition of distributed containment control for delayed multi-agent systems is derived with the aid of Lyapunov–Krasovskii function. Simulation results are provided to prove the correctness and effectiveness of the conclusion.
基金Supported by the National Excellence Youth Science Foundation of China under Grant No.60925012the National Basic Research Science Program of China under Grant No.2012CB720000+3 种基金973 Programthe National Natural Science Foundation of China under Grant Nos.60875039,60904022,60805039,and 60774013the Science Foundation of China postdoctoral under Grant No.2011M500205the Natural Science Foundation of Shandong Province of China under Grant No.ZR2011FM017
文摘The objective of this paper is to investigate the consensus of the multi-agent systems w/th nonlinear coupling function and external disturbances. The disturbance includes two parts, one part is supposed to be generated by an exogenous system, which is not required to be neutrally stable as in the output regulation theory, the other part is the modeling uncertainty in the exogenous disturbance system. A novel composite disturbance observer based control （DOBC） and H∞ control scheme is presented so that the disturbance with the exogenous system can be estimated and compensated and the consensus of the multi-agent systems with fixed and switching graph can be reached by using Hoo control law. Simulations demonstrate the advantages of the proposed DOBC and H∞ control scheme.
基金This work was supported by the National Natural Science Foundation of China(Nos.61973189,62073190)the Research Fund for the Taishan Scholar Project of Shandong Province of China(No.ts20190905)the Natural Science Foundation of Shandong Province of China(No.ZR2020ZD25).
文摘In this paper,the bipartite consensus problem is studied for a class of uncertain high-order nonlinear multi-agent systems.A signed digraph is presented to describe the collaborative and competitive interactions among agents.For each agent with lower triangular structure,a time-varying gain compensator is first designed by relative output information of neighboring agents.Subsequently,a distributed controller with dynamic event-triggered mechanism is proposed to drive the bipartite consensus error to zero.It is worth noting that an internal dynamic variable is introduced in triggering function,which plays an essential role in excluding the Zeno behavior and reducing energy consumption.Furthermore,the dynamic event-triggered control protocol is developed for upper triangular multi-agent systems to realize the bipartite consensus without Zeno behavior.Finally,simulation examples are provided to illustrate the effectiveness of the presented results.
基金supported by the National Natural Science Foundation of China(61303211)Zhejiang Provincial Natural Science Foundation of China(LY17F030003,LY15F030009)
文摘In this paper, the leader-following tracking problem of fractional-order multi-agent systems is addressed. The dynamics of each agent may be heterogeneous and has unknown nonlinearities. By assumptions that the interaction topology is undirected and connected and the unknown nonlinear uncertain dynamics can be parameterized by a neural network, an adaptive learning law is proposed to deal with unknown nonlinear dynamics, based on which a kind of cooperative tracking protocols are constructed. The feedback gain matrix is obtained to solve an algebraic Riccati equation. To construct the fully distributed cooperative tracking protocols, the adaptive law is also adopted to adjust the coupling weight. With the developed control laws,we can prove that all signals in the closed-loop systems are guaranteed to be uniformly ultimately bounded. Finally, a simple simulation example is provided to illustrate the established result.
基金supported in part by the National Natural Science Foundation of China(61473195,61603081,61773131,61773056,61873306,U1966202,61803305,61873338)the China Postdoctoral Science Foundation(2015M580513)Research Fund for the Taishan Scholar Project of Shandong Province of China(TSQN201812052)。
文摘In this paper, we consider the distributed adaptive fault-tolerant output regulation problem for heterogeneous multiagent systems with matched system uncertainties and mismatched coupling uncertainties among subsystems under the influence of actuator faults. First, distributed finite-time observers are proposed for all subsystems to observe the state of the exosystem. Then, a novel fault-tolerant controller is designed to compensate for the influence of matched system uncertainties and actuator faults. By using the linear matrix inequality technique, a sufficient condition is provided to guarantee the solvability of the considered problem in the presence of mismatched coupling uncertainties. Moreover, it is shown that the system in closed-loop with the developed controller can achieve output regulation by using the Lyapunov stability theory and cyclic-small-gain theory.Finally, a numerical example is given to illustrate the effectiveness of the obtained result.
基金The National Natural Science Foundation of China(62136008,62293541)The Beijing Natural Science Foundation(4232056)The Beijing Nova Program(20240484514).
文摘Cooperative multi-agent reinforcement learning(MARL)is a key technology for enabling cooperation in complex multi-agent systems.It has achieved remarkable progress in areas such as gaming,autonomous driving,and multi-robot control.Empowering cooperative MARL with multi-task decision-making capabilities is expected to further broaden its application scope.In multi-task scenarios,cooperative MARL algorithms need to address 3 types of multi-task problems:reward-related multi-task,arising from different reward functions;multi-domain multi-task,caused by differences in state and action spaces,state transition functions;and scalability-related multi-task,resulting from the dynamic variation in the number of agents.Most existing studies focus on scalability-related multitask problems.However,with the increasing integration between large language models(LLMs)and multi-agent systems,a growing number of LLM-based multi-agent systems have emerged,enabling more complex multi-task cooperation.This paper provides a comprehensive review of the latest advances in this field.By combining multi-task reinforcement learning with cooperative MARL,we categorize and analyze the 3 major types of multi-task problems under multi-agent settings,offering more fine-grained classifications and summarizing key insights for each.In addition,we summarize commonly used benchmarks and discuss future directions of research in this area,which hold promise for further enhancing the multi-task cooperation capabilities of multi-agent systems and expanding their practical applications in the real world.
基金The National Natural Science Foundation of China(W2431048)The Science and Technology Research Program of Chongqing Municipal Education Commission,China(KJZDK202300807)The Chongqing Natural Science Foundation,China(CSTB2024NSCQQCXMX0052).
文摘This paper addresses the consensus problem of nonlinear multi-agent systems subject to external disturbances and uncertainties under denial-ofservice(DoS)attacks.Firstly,an observer-based state feedback control method is employed to achieve secure control by estimating the system's state in real time.Secondly,by combining a memory-based adaptive eventtriggered mechanism with neural networks,the paper aims to approximate the nonlinear terms in the networked system and efficiently conserve system resources.Finally,based on a two-degree-of-freedom model of a vehicle affected by crosswinds,this paper constructs a multi-unmanned ground vehicle(Multi-UGV)system to validate the effectiveness of the proposed method.Simulation results show that the proposed control strategy can effectively handle external disturbances such as crosswinds in practical applications,ensuring the stability and reliable operation of the Multi-UGV system.
文摘In this paper, we study the leader-following rendezvous and flocking problems for a class of second-order nonlinear multi- agent systems, which contain both external disturbances and plant uncertainties. What differs our problems from the conventional leader-following consensus problem is that we need to preserve the connectivity of the communication graph instead of assuming the connectivity of the communication graph. By integrating the adaptive control technique, the distributed observer method and the potential function method, the two problems are both solved. Finally, we apply our results to a group of van der Pol oscillators.
文摘This paper studies the leader-following consensus problem for a class of second-order nonlinear multi-agent systems subject to linearly parameterized uncertainty and disturbance. The problem is solved by integrating the adaptive control technique and the adaptive distributed observer method. The design procedure is illustrated by an example with a group of Van der Pol oscillators as the followers and a harmonic system as the leader.
基金This work was supported by Tianjin Natural Science Foundation of China(20JCYBJC01060,20JCQNJC01450)the National Natural Science Foundation of China(61973175)Tianjin Postgraduate Scientific Research and Innovation Project(2020YJSZXB03,2020YJSZXB12).
文摘In this paper,the distributed fuzzy fault-tolerant tracking consensus problem of leader-follower multi-agent systems(MASs)is studied.The objective system includes actuator faults,mismatched parameter uncertainties,nonlinear functions,and exogenous disturbances under switching communication topologies.To solve this problem,a distributed fuzzy fault-tolerant controller is proposed for each follower by adaptive mechanisms to track the state of the leader.Furthermore,the fuzzy logic system is utilized to approximate the unknown nonlinear dynamics.An error estimator is introduced between the mismatched parameter matrix and the input matrix.Then,a selective adaptive law with relative state information is adopted and applied.When calculating the Lyapunov function’s derivative,the coupling terms related to consensus error and mismatched parameter uncertainties can be eliminated.Finally,a numerical simulation is given to validate the effectiveness of the proposed protocol.
基金supported in part by the National Natural Science Foundation of China(Nos.61673081,51979020,51909021,51939001)in part by Science and Technology Fund for Distinguished Young Scholars of Dalian(No.2018RJ08)+5 种基金in part by the Stable Supporting Fund of Science and Technology on Underwater Vehicle Technology(No.JCKYS2019604SXJQR-01)in part by the Supporting Program for High-level Talent in Transportation Department(No.2018-030)in part by the National Key Research and Development Program of China(No.2016YFC0301500)in part by the Fundamental Research Funds for the Central Universities(Nos.3132019319,3132020101,3132020102)in part by China Postdoctoral Science Foundation(No.2019M650086)the Training Program for Doctoral Innovative Talents of DLMU(No.CXXM2019BS001)。
文摘This paper is concerned with distributed containment maneuvering of second-order Multi-Input Multi-Output(MIMO)multi-agent systems with non-periodic communication and actuation.The agent is subject to unmatched nonlinear dynamics and external disturbances.Event-triggered containment maneuvering control methods is developed based on a modular design.Specifically,an estimator module is constructed based on neural networks and the nonperiodic obtained follower information through event-triggered communication.Next,a controller module is designed by using the identified information from the estimator module and a third-order linear tracking differentiator.An event-triggered mechanism is introduced for updating the actuator.Then,a path update law is designed based on the non-periodic leader information through event-triggered communication.The closed-loop system cascaded by the estimation subsystem and control subsystem is proved to be input-to-state stable,and Zeno behavior is excluded in the control process.The proposed method is capable of reducing the consumption of communication and actuation.A simulation example is provided to substantiate the effectiveness of the proposed event-triggered control method for distributed containment maneuvering of second-order MIMO multi-agent systems.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.61074159 and 61703286)
文摘We propose a new approach to discuss the consensus problem of multi-agent systems with time-varying delayed control inputs, switching topologies, and stochastic cyber-attacks under hybrid-triggered mechanism.A Bernoulli variable is used to describe the hybrid-triggered scheme, which is introduced to alleviate the burden of the network.The mathematical model of the closed-loop control system is established by taking the influences of time-varying delayed control inputs,switching topologies, and stochastic cyber-attacks into account under the hybrid-triggered scheme.A theorem as the main result is given to make the system consistent based on the theory of Lyapunov stability and linear matrix inequality.Markov jumps with uncertain rates of transitions are applied to describe the switch of topologies.Finally, a simulation example demonstrates the feasibility of the theory in this paper.
基金supported by the National Natural Science Foundation of China(Nos.12272104,U22B2013).
文摘This paper investigates the challenges associated with Unmanned Aerial Vehicle (UAV) collaborative search and target tracking in dynamic and unknown environments characterized by limited field of view. The primary objective is to explore the unknown environments to locate and track targets effectively. To address this problem, we propose a novel Multi-Agent Reinforcement Learning (MARL) method based on Graph Neural Network (GNN). Firstly, a method is introduced for encoding continuous-space multi-UAV problem data into spatial graphs which establish essential relationships among agents, obstacles, and targets. Secondly, a Graph AttenTion network (GAT) model is presented, which focuses exclusively on adjacent nodes, learns attention weights adaptively and allows agents to better process information in dynamic environments. Reward functions are specifically designed to tackle exploration challenges in environments with sparse rewards. By introducing a framework that integrates centralized training and distributed execution, the advancement of models is facilitated. Simulation results show that the proposed method outperforms the existing MARL method in search rate and tracking performance with less collisions. The experiments show that the proposed method can be extended to applications with a larger number of agents, which provides a potential solution to the challenging problem of multi-UAV autonomous tracking in dynamic unknown environments.
