This paper investigates the consensus tracking control problem for high order nonlinear multi-agent systems subject to non-affine faults,partial measurable states,uncertain control coefficients,and unknown external di...This paper investigates the consensus tracking control problem for high order nonlinear multi-agent systems subject to non-affine faults,partial measurable states,uncertain control coefficients,and unknown external disturbances.Under the directed topology conditions,an observer-based finite-time control strategy based on adaptive backstepping and is proposed,in which a neural network-based state observer is employed to approximate the unmeasurable system state variables.To address the complexity explosion problem associated with the backstepping method,a finite-time command filter is incorporated,with error compensation signals designed to mitigate the filter-induced errors.Additionally,the Butterworth low-pass filter is introduced to avoid the algebraic ring problem in the design of the controller.The finite-time stability of the closed-loop system is rigorously analyzed with the finite-time Lyapunov stability criterion,validating that all closed-loop signals of the system remain bounded within a finite time.Finally,the effectiveness of the proposed control strategy is verified through a simulation example.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
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
This paper mainly focuses on the velocity-constrained consensus problem of discrete-time heterogeneous multi-agent systems with nonconvex constraints and arbitrarily switching topologies,where each agent has first-ord...This paper mainly focuses on the velocity-constrained consensus problem of discrete-time heterogeneous multi-agent systems with nonconvex constraints and arbitrarily switching topologies,where each agent has first-order or second-order dynamics.To solve this problem,a distributed algorithm is proposed based on a contraction operator.By employing the properties of the stochastic matrix,it is shown that all agents’position states could converge to a common point and second-order agents’velocity states could remain in corresponding nonconvex constraint sets and converge to zero as long as the joint communication topology has one directed spanning tree.Finally,the numerical simulation results are provided to verify the effectiveness of the proposed algorithms.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
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 paper proposes a Multi-Agent Attention Proximal Policy Optimization(MA2PPO)algorithm aiming at the problems such as credit assignment,low collaboration efficiency and weak strategy generalization ability existing...This paper proposes a Multi-Agent Attention Proximal Policy Optimization(MA2PPO)algorithm aiming at the problems such as credit assignment,low collaboration efficiency and weak strategy generalization ability existing in the cooperative pursuit tasks of multiple unmanned aerial vehicles(UAVs).Traditional algorithms often fail to effectively identify critical cooperative relationships in such tasks,leading to low capture efficiency and a significant decline in performance when the scale expands.To tackle these issues,based on the proximal policy optimization(PPO)algorithm,MA2PPO adopts the centralized training with decentralized execution(CTDE)framework and introduces a dynamic decoupling mechanism,that is,sharing the multi-head attention(MHA)mechanism for critics during centralized training to solve the credit assignment problem.This method enables the pursuers to identify highly correlated interactions with their teammates,effectively eliminate irrelevant and weakly relevant interactions,and decompose large-scale cooperation problems into decoupled sub-problems,thereby enhancing the collaborative efficiency and policy stability among multiple agents.Furthermore,a reward function has been devised to facilitate the pursuers to encircle the escapee by combining a formation reward with a distance reward,which incentivizes UAVs to develop sophisticated cooperative pursuit strategies.Experimental results demonstrate the effectiveness of the proposed algorithm in achieving multi-UAV cooperative pursuit and inducing diverse cooperative pursuit behaviors among UAVs.Moreover,experiments on scalability have demonstrated that the algorithm is suitable for large-scale multi-UAV systems.展开更多
This paper proposes an output-feedback based prescribed performance consensus tracking control methodology for a class of heterogeneous multi-agent systems(HMASs)with inconsistent system structure,where the performanc...This paper proposes an output-feedback based prescribed performance consensus tracking control methodology for a class of heterogeneous multi-agent systems(HMASs)with inconsistent system structure,where the performance behavior is allowed to be different from that of each other.Both the heterogeneous system structures and the nonidentical performance requirements make the control problem much more challenging than that of MASs with identical structure and performance requirement.This is mainly due to the coupling effect of the system dynamics and performance restriction of each agent in the cooperative control action.The key to solve this problem is to introduce a dual-phase performance-guaranteed method,in which the consensus tracking error is decomposed into auxiliary tracking error and filter tracking error and then the whole performance control is decomposed into two phases.By confining the two errors respectively,the practical tracking error can be proved to be explicitly confined within an arbitrarily given performance envelope by merely adjusting the design parameters rather than modifying control structure.Moreover,the prescribed performance control(PPC)result is not only uniform with any initial conditions and design parameters,allowing it to be global,but also unifying both the global and semi-global result into one frame,distinguishing itself from most existing PPC works where either only global or only semi-global result is guaranteed.Finally,the effectiveness of the proposed control scheme is confirmed by the simulation conducted on a group of tunnel-diode circuits(TDC).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
Both evolutionary computation(EC)and multiagent systems(MAS)study the emergence of intelligence through the interaction and cooperation of a group of individuals.EC focuses on solving various complex optimization prob...Both evolutionary computation(EC)and multiagent systems(MAS)study the emergence of intelligence through the interaction and cooperation of a group of individuals.EC focuses on solving various complex optimization problems,while MAS provides a flexible model for distributed artificial intelligence.Since their group interaction mechanisms can be borrowed from each other,many studies have attempted to combine EC and MAS.With the rapid development of the Internet of Things,the confluence of EC and MAS has become more and more important,and related articles have shown a continuously growing trend during the last decades.In this survey,we first elaborate on the mutual assistance of EC and MAS from two aspects,agent-based EC and EC-assisted MAS.Agent-based EC aims to introduce characteristics of MAS into EC to improve the performance and parallelism of EC,while EC-assisted MAS aims to use EC to better solve optimization problems in MAS.Furthermore,we review studies that combine the cooperation mechanisms of EC and MAS,which greatly leverage the strengths of both sides.A description framework is built to elaborate existing studies.Promising future research directions are also discussed in conjunction with emerging technologies and real-world applications.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
Multimodal dialogue systems often fail to maintain coherent reasoning over extended conversations and suffer from hallucination due to limited context modeling capabilities.Current approaches struggle with crossmodal ...Multimodal dialogue systems often fail to maintain coherent reasoning over extended conversations and suffer from hallucination due to limited context modeling capabilities.Current approaches struggle with crossmodal alignment,temporal consistency,and robust handling of noisy or incomplete inputs across multiple modalities.We propose Multi Agent-Chain of Thought(CoT),a novel multi-agent chain-of-thought reasoning framework where specialized agents for text,vision,and speech modalities collaboratively construct shared reasoning traces through inter-agent message passing and consensus voting mechanisms.Our architecture incorporates self-reflection modules,conflict resolution protocols,and dynamic rationale alignment to enhance consistency,factual accuracy,and user engagement.The framework employs a hierarchical attention mechanism with cross-modal fusion and implements adaptive reasoning depth based on dialogue complexity.Comprehensive evaluations on Situated Interactive Multi-Modal Conversations(SIMMC)2.0,VisDial v1.0,and newly introduced challenging scenarios demonstrate statistically significant improvements in grounding accuracy(p<0.01),chain-of-thought interpretability,and robustness to adversarial inputs compared to state-of-the-art monolithic transformer baselines and existing multi-agent approaches.展开更多
Cyber attacks pose severe threats on synchronization of multi-agent systems.Deception attack,as a typical type of cyber attack,can bypass the surveillance of the attack detection mechanism silently,resulting in a heav...Cyber attacks pose severe threats on synchronization of multi-agent systems.Deception attack,as a typical type of cyber attack,can bypass the surveillance of the attack detection mechanism silently,resulting in a heavy loss.Therefore,the problem of mean-square bounded synchronization in multi-agent systems subject to deception attacks is investigated in this paper.The control signals can be replaced with false data from controllerto-actuator channels or the controller.The success of the attack is measured through a stochastic variable.A distributed impulsive controller using a pinning strategy is redesigned,which ensures that mean-square bounded synchronization is achieved in the presence of deception attacks.Some sufficient conditions are derived,in which upper bounds of the synchronization error are given.Finally,two numerical simulations with symmetric and asymmetric network topologies are given to illustrate the theoretical results.展开更多
The paper proposes a novel approach for formationcontainment control based on a dynamic event-triggering mechanism for multi-agent systems.The leader-leader and follower-follower communications are reduced by utilizin...The paper proposes a novel approach for formationcontainment control based on a dynamic event-triggering mechanism for multi-agent systems.The leader-leader and follower-follower communications are reduced by utilizing the distributed dynamic event-triggered framework.We consider two separate sets of design parameters:one set comprising control and dynamic event-triggering parameters for the leaders and a second set similar to the first one with different values for the followers.The proposed algorithm includes two novel stages of codesign optimization to simultaneously compute the two sets of parameters.The design optimizations are convex and use the weighted sum approach to enable a structured trade-off between the formation-containment convergence rate and associated communications.Simulations based on non-holonomic mobile robot multi-agent systems quantify the effectiveness of the proposed approach.展开更多
This paper investigates the consensus problem for linear multi-agent systems with the heterogeneous disturbances generated by the Brown motion.Its main contribution is that a control scheme is designed to achieve the ...This paper investigates the consensus problem for linear multi-agent systems with the heterogeneous disturbances generated by the Brown motion.Its main contribution is that a control scheme is designed to achieve the dynamic consensus for the multi-agent systems in directed topology interfered by stochastic noise.In traditional ways,the coupling weights depending on the communication structure are static.A new distributed controller is designed based on Riccati inequalities,while updating the coupling weights associated with the gain matrix by state errors between adjacent agents.By introducing time-varying coupling weights into this novel control law,the state errors between leader and followers asymptotically converge to the minimum value utilizing the local interaction.Through the Lyapunov directed method and It?formula,the stability of the closed-loop system with the proposed control law is analyzed.Two simulation results conducted by the new and traditional schemes are presented to demonstrate the effectiveness and advantage of the developed control method.展开更多
Consensus problem is investigated for heterogeneous multi-agent systems composed of first-order agents and second-order agents in this paper. Leader-following consensus protocol is adopted to solve consensus problem o...Consensus problem is investigated for heterogeneous multi-agent systems composed of first-order agents and second-order agents in this paper. Leader-following consensus protocol is adopted to solve consensus problem of heterogeneous multi-agent systems with time-varying communication and input delays. By constructing Lyapunov-Krasovkii functional, sufficient consensus conditions in linear matrix inequality(LMI) form are obtained for the system under fixed interconnection topology. Moreover, consensus conditions are also obtained for the heterogeneous systems under switching topologies with time delays. Simulation examples are given to illustrate effectiveness of the results.展开更多
We consider an anisotropic swarm model with an attraction/repulsion function and study its aggregation properties. It is shown that the swarm members will aggregate and eventually form a cohesive cluster of finite siz...We consider an anisotropic swarm model with an attraction/repulsion function and study its aggregation properties. It is shown that the swarm members will aggregate and eventually form a cohesive cluster of finite size around the swarm center in a finite time. Moreover, we extend our results to more general attraction/repulsion functions. Numerical simulations demonstrate that all agents will eventually enter into and remain in a bounded region around the swarm center which may exhibit complex spiral motion due to asymmetry of the coupling structure. The model in this paper is more general than isotropic swarms and our results provide further insight into the effect of the interaction pattern on individual motion in a swarm system.展开更多
This paper studies the consensus problems for a group of agents with switching topology and time-varying communication delays,where the dynamics of agents is modeled as a high-order integrator.A linear distributed con...This paper studies the consensus problems for a group of agents with switching topology and time-varying communication delays,where the dynamics of agents is modeled as a high-order integrator.A linear distributed consensus protocol is proposed,which only depends on the agent's own information and its neighbors'partial information.By introducing a decomposition of the state vector and performing a state space transformation,the closed-loop dynamics of the multi-agent system is converted into two decoupled subsystems.Based on the decoupled subsystems,some sufficient conditions for the convergence to consensus are established,which provide the upper bounds on the admissible communication delays.Also,the explicit expression of the consensus state is derived.Moreover,the results on the consensus seeking of the group of high-order agents have been extended to a network of agents with dynamics modeled as a completely controllable linear time-invariant system.It is proved that the convergence to consensus of this network is equivalent to that of the group of high-order agents.Finally,some numerical examples are given to demonstrate the effectiveness of the main results.展开更多
基金supported in part by the Beijing Natural Science Foundation under Grant 4252050in part by the National Science Fund for Distinguished Young Scholars under Grant 62425304in part by the Basic Science Center Programs of NSFC under Grant 62088101.
文摘This paper investigates the consensus tracking control problem for high order nonlinear multi-agent systems subject to non-affine faults,partial measurable states,uncertain control coefficients,and unknown external disturbances.Under the directed topology conditions,an observer-based finite-time control strategy based on adaptive backstepping and is proposed,in which a neural network-based state observer is employed to approximate the unmeasurable system state variables.To address the complexity explosion problem associated with the backstepping method,a finite-time command filter is incorporated,with error compensation signals designed to mitigate the filter-induced errors.Additionally,the Butterworth low-pass filter is introduced to avoid the algebraic ring problem in the design of the controller.The finite-time stability of the closed-loop system is rigorously analyzed with the finite-time Lyapunov stability criterion,validating that all closed-loop signals of the system remain bounded within a finite time.Finally,the effectiveness of the proposed control strategy is verified through a simulation example.
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.
基金2024 Jiangsu Province Youth Science and Technology Talent Support Project2024 Yancheng Key Research and Development Plan(Social Development)projects,“Research and Application of Multi Agent Offline Distributed Trust Perception Virtual Wireless Sensor Network Algorithm”and“Research and Application of a New Type of Fishery Ship Safety Production Monitoring Equipment”。
文摘This paper mainly focuses on the velocity-constrained consensus problem of discrete-time heterogeneous multi-agent systems with nonconvex constraints and arbitrarily switching topologies,where each agent has first-order or second-order dynamics.To solve this problem,a distributed algorithm is proposed based on a contraction operator.By employing the properties of the stochastic matrix,it is shown that all agents’position states could converge to a common point and second-order agents’velocity states could remain in corresponding nonconvex constraint sets and converge to zero as long as the joint communication topology has one directed spanning tree.Finally,the numerical simulation results are provided to verify the effectiveness of the proposed algorithms.
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supported in part by the National Natural Science Foundation of China under Grant 6237319in part by the Postgraduate Research and Practice Innovation Program of Jiangsu Province under Grant KYCX230479.
文摘Formation control in multi-agent systems has become a critical area of interest due to its wide-ranging applications in robotics,autonomous transportation,and surveillance.While various studies have explored distributed cooperative control,this review focuses on the theoretical foundations and recent developments in formation control strategies.The paper categorizes and analyzes key formation types,including formation maintenance,group or cluster formation,bipartite formations,event-triggered formations,finite-time convergence,and constrained formations.A significant portion of the review addresses formation control under constrained dynamics,presenting both modelbased and model-free approaches that consider practical limitations such as actuator bounds,communication delays,and nonholonomic constraints.Additionally,the paper discusses emerging trends,including the integration of eventdriven mechanisms and AI-enhanced coordination strategies.Comparative evaluations highlight the trade-offs among various methodologies regarding scalability,robustness,and real-world feasibility.Practical implementations are reviewed across diverse platforms,and the review identifies the current achievements and unresolved challenges in the field.The paper concludes by outlining promising research directions,such as adaptive control for dynamic environments,energy-efficient coordination,and using learning-based control under uncertainty.This review synthesizes the current state of the art and provides a road map for future investigation,making it a valuable reference for researchers and practitioners aiming to advance formation control in multi-agent systems.
基金supported by the National Research and Development Program of China under Grant JCKY2018607C019in part by the Key Laboratory Fund of UAV of Northwestern Polytechnical University under Grant 2021JCJQLB0710L.
文摘This paper proposes a Multi-Agent Attention Proximal Policy Optimization(MA2PPO)algorithm aiming at the problems such as credit assignment,low collaboration efficiency and weak strategy generalization ability existing in the cooperative pursuit tasks of multiple unmanned aerial vehicles(UAVs).Traditional algorithms often fail to effectively identify critical cooperative relationships in such tasks,leading to low capture efficiency and a significant decline in performance when the scale expands.To tackle these issues,based on the proximal policy optimization(PPO)algorithm,MA2PPO adopts the centralized training with decentralized execution(CTDE)framework and introduces a dynamic decoupling mechanism,that is,sharing the multi-head attention(MHA)mechanism for critics during centralized training to solve the credit assignment problem.This method enables the pursuers to identify highly correlated interactions with their teammates,effectively eliminate irrelevant and weakly relevant interactions,and decompose large-scale cooperation problems into decoupled sub-problems,thereby enhancing the collaborative efficiency and policy stability among multiple agents.Furthermore,a reward function has been devised to facilitate the pursuers to encircle the escapee by combining a formation reward with a distance reward,which incentivizes UAVs to develop sophisticated cooperative pursuit strategies.Experimental results demonstrate the effectiveness of the proposed algorithm in achieving multi-UAV cooperative pursuit and inducing diverse cooperative pursuit behaviors among UAVs.Moreover,experiments on scalability have demonstrated that the algorithm is suitable for large-scale multi-UAV systems.
基金supported in part by the National Key Research and Development Program of China(2023YFA1011803)the National Natural Science Foundation of China(62273064,W2411061)+1 种基金the Chongqing Natural Science Foundation(CSTB2023NSCQ-MSX0588),the Innovation Support Program for International Students Returning to China(cx2022016)the Central University Project(2023CDJKYJH047).
文摘This paper proposes an output-feedback based prescribed performance consensus tracking control methodology for a class of heterogeneous multi-agent systems(HMASs)with inconsistent system structure,where the performance behavior is allowed to be different from that of each other.Both the heterogeneous system structures and the nonidentical performance requirements make the control problem much more challenging than that of MASs with identical structure and performance requirement.This is mainly due to the coupling effect of the system dynamics and performance restriction of each agent in the cooperative control action.The key to solve this problem is to introduce a dual-phase performance-guaranteed method,in which the consensus tracking error is decomposed into auxiliary tracking error and filter tracking error and then the whole performance control is decomposed into two phases.By confining the two errors respectively,the practical tracking error can be proved to be explicitly confined within an arbitrarily given performance envelope by merely adjusting the design parameters rather than modifying control structure.Moreover,the prescribed performance control(PPC)result is not only uniform with any initial conditions and design parameters,allowing it to be global,but also unifying both the global and semi-global result into one frame,distinguishing itself from most existing PPC works where either only global or only semi-global result is guaranteed.Finally,the effectiveness of the proposed control scheme is confirmed by the simulation conducted on a group of tunnel-diode circuits(TDC).
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 Key Research and Development Project(2023YFE0206200)the National Natural Science Foundation of China(U23B2058)+3 种基金in part by Guangdong Regional Joint Foundation Key Project(2022B1515120076)the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(RS-2025-00555463&RS-2025-25456394)the Tianjin Top Scientist Studio Project(24JRRCRC00030)the Tianjin Belt and Road Joint Laboratory(24PTLYHZ00250).
文摘Both evolutionary computation(EC)and multiagent systems(MAS)study the emergence of intelligence through the interaction and cooperation of a group of individuals.EC focuses on solving various complex optimization problems,while MAS provides a flexible model for distributed artificial intelligence.Since their group interaction mechanisms can be borrowed from each other,many studies have attempted to combine EC and MAS.With the rapid development of the Internet of Things,the confluence of EC and MAS has become more and more important,and related articles have shown a continuously growing trend during the last decades.In this survey,we first elaborate on the mutual assistance of EC and MAS from two aspects,agent-based EC and EC-assisted MAS.Agent-based EC aims to introduce characteristics of MAS into EC to improve the performance and parallelism of EC,while EC-assisted MAS aims to use EC to better solve optimization problems in MAS.Furthermore,we review studies that combine the cooperation mechanisms of EC and MAS,which greatly leverage the strengths of both sides.A description framework is built to elaborate existing studies.Promising future research directions are also discussed in conjunction with emerging technologies and real-world applications.
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.
文摘Multimodal dialogue systems often fail to maintain coherent reasoning over extended conversations and suffer from hallucination due to limited context modeling capabilities.Current approaches struggle with crossmodal alignment,temporal consistency,and robust handling of noisy or incomplete inputs across multiple modalities.We propose Multi Agent-Chain of Thought(CoT),a novel multi-agent chain-of-thought reasoning framework where specialized agents for text,vision,and speech modalities collaboratively construct shared reasoning traces through inter-agent message passing and consensus voting mechanisms.Our architecture incorporates self-reflection modules,conflict resolution protocols,and dynamic rationale alignment to enhance consistency,factual accuracy,and user engagement.The framework employs a hierarchical attention mechanism with cross-modal fusion and implements adaptive reasoning depth based on dialogue complexity.Comprehensive evaluations on Situated Interactive Multi-Modal Conversations(SIMMC)2.0,VisDial v1.0,and newly introduced challenging scenarios demonstrate statistically significant improvements in grounding accuracy(p<0.01),chain-of-thought interpretability,and robustness to adversarial inputs compared to state-of-the-art monolithic transformer baselines and existing multi-agent approaches.
基金supported by the National Natural Science Foundation of China(61988101,61922030,61773163)Shanghai Rising-Star Program(18QA1401400)+3 种基金the International(Regional)Cooperation and Exchange Project(61720106008)the Natural Science Foundation of Shanghai(17ZR1406800)the Fundamental Research Funds for the Central Universitiesthe 111 Project(B17017)。
文摘Cyber attacks pose severe threats on synchronization of multi-agent systems.Deception attack,as a typical type of cyber attack,can bypass the surveillance of the attack detection mechanism silently,resulting in a heavy loss.Therefore,the problem of mean-square bounded synchronization in multi-agent systems subject to deception attacks is investigated in this paper.The control signals can be replaced with false data from controllerto-actuator channels or the controller.The success of the attack is measured through a stochastic variable.A distributed impulsive controller using a pinning strategy is redesigned,which ensures that mean-square bounded synchronization is achieved in the presence of deception attacks.Some sufficient conditions are derived,in which upper bounds of the synchronization error are given.Finally,two numerical simulations with symmetric and asymmetric network topologies are given to illustrate the theoretical results.
基金partially supported by the Natural Sciencesand Engineering Research Council(NSERC)of Canada through the NSERC Discovery(RGPIN-2016-04988)。
文摘The paper proposes a novel approach for formationcontainment control based on a dynamic event-triggering mechanism for multi-agent systems.The leader-leader and follower-follower communications are reduced by utilizing the distributed dynamic event-triggered framework.We consider two separate sets of design parameters:one set comprising control and dynamic event-triggering parameters for the leaders and a second set similar to the first one with different values for the followers.The proposed algorithm includes two novel stages of codesign optimization to simultaneously compute the two sets of parameters.The design optimizations are convex and use the weighted sum approach to enable a structured trade-off between the formation-containment convergence rate and associated communications.Simulations based on non-holonomic mobile robot multi-agent systems quantify the effectiveness of the proposed approach.
基金supported in part by the National Natural Science Foundation of China(61722312,61533017,62073321)the National Key Research and Development Program of China(2018YFB1702300)。
文摘This paper investigates the consensus problem for linear multi-agent systems with the heterogeneous disturbances generated by the Brown motion.Its main contribution is that a control scheme is designed to achieve the dynamic consensus for the multi-agent systems in directed topology interfered by stochastic noise.In traditional ways,the coupling weights depending on the communication structure are static.A new distributed controller is designed based on Riccati inequalities,while updating the coupling weights associated with the gain matrix by state errors between adjacent agents.By introducing time-varying coupling weights into this novel control law,the state errors between leader and followers asymptotically converge to the minimum value utilizing the local interaction.Through the Lyapunov directed method and It?formula,the stability of the closed-loop system with the proposed control law is analyzed.Two simulation results conducted by the new and traditional schemes are presented to demonstrate the effectiveness and advantage of the developed control method.
基金supported by National Natural Science Foundation of China(Nos.61104092,61134007 and 61203147)the Priority Academic Program Development of Jiangsu Higher Education Institutions
文摘Consensus problem is investigated for heterogeneous multi-agent systems composed of first-order agents and second-order agents in this paper. Leader-following consensus protocol is adopted to solve consensus problem of heterogeneous multi-agent systems with time-varying communication and input delays. By constructing Lyapunov-Krasovkii functional, sufficient consensus conditions in linear matrix inequality(LMI) form are obtained for the system under fixed interconnection topology. Moreover, consensus conditions are also obtained for the heterogeneous systems under switching topologies with time delays. Simulation examples are given to illustrate effectiveness of the results.
基金This work was supported by the National Natural Science Foundation of China (No. 10372002,60274001) and the National Key Basic Research and Develop-ment Program (No.2002CB312200).
文摘We consider an anisotropic swarm model with an attraction/repulsion function and study its aggregation properties. It is shown that the swarm members will aggregate and eventually form a cohesive cluster of finite size around the swarm center in a finite time. Moreover, we extend our results to more general attraction/repulsion functions. Numerical simulations demonstrate that all agents will eventually enter into and remain in a bounded region around the swarm center which may exhibit complex spiral motion due to asymmetry of the coupling structure. The model in this paper is more general than isotropic swarms and our results provide further insight into the effect of the interaction pattern on individual motion in a swarm system.
基金supported by the National Natural Science Foundation of China(No.60674050,60736022,10972002,60774089,60704039)
文摘This paper studies the consensus problems for a group of agents with switching topology and time-varying communication delays,where the dynamics of agents is modeled as a high-order integrator.A linear distributed consensus protocol is proposed,which only depends on the agent's own information and its neighbors'partial information.By introducing a decomposition of the state vector and performing a state space transformation,the closed-loop dynamics of the multi-agent system is converted into two decoupled subsystems.Based on the decoupled subsystems,some sufficient conditions for the convergence to consensus are established,which provide the upper bounds on the admissible communication delays.Also,the explicit expression of the consensus state is derived.Moreover,the results on the consensus seeking of the group of high-order agents have been extended to a network of agents with dynamics modeled as a completely controllable linear time-invariant system.It is proved that the convergence to consensus of this network is equivalent to that of the group of high-order agents.Finally,some numerical examples are given to demonstrate the effectiveness of the main results.
