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The predefined-time cooperative output regulation of second-order nonlinear multiagent systems with an unknown exosystem is investigated in this paper. Existing similar work is almost limited to exactly known exosystems, and the upper bound of convergence time for closed-loop systems is difficult to adjust and predict, which may not meet practical needs. In this paper, we first propose a new dynamic compensator called predefined-time distributed observer, which guarantees that each agent estimates the state and parameters about the linear exosystem with unknown system matrix through the general directed communication network within the time set by an explicit parameter. Subsequently, combining the improved dynamic gain control method and the proposed predefined-time distributed observer, a novel distributed dynamic predefined-time control scheme is proposed, which solves the problem of this paper by simplifying the tedious arithmetic process caused by the traditional backstepping method. The final simulation experiments verify the effectiveness of the proposed control scheme. • We extended similar articles to more general leader and controlled objects. • The settling time of our controller can be set directly and structure is simple. • We present a new distributed observer for unknown leader and general digraph. • The designed observer can work for an arbitrarily set period of time. • We transform an unknown leader into a known one in a predefined time. [ABSTRACT FROM AUTHOR]

This paper studies the consensus problem of a new multi-agent system via multi-task, multi-control mechanism and multi-consensus strategy. Firstly, two multi-task algorithms are proposed, which can reasonably select some agent nodes with better performance to form the multi-agent system according to different tasks. Secondly, a multi-control protocol designed in this paper integrates continuous control mechanism, impulsive control mechanism and hybrid control mechanism, which has strong applicability and efficiency. Thirdly, a multi-consensus strategy is designed, and it can be converted into "average consensus strategy", "leader-following consensus strategy" and "hybrid consensus strategy" through different parameter settings, which greatly broadens the application field of the multi-agent system. We construct a dynamic model for the proposed multi-agent system, analyze it by using matrix measure and Lyapunov stability theory, and obtain the theorems that enable it to achieve multiple consensus. Finally, the efficiency and practicability of our theories are verified through several simulation experiments. We further carry out some comparative analysis with some relevant papers, and obtain the superiority of our theories in multiple indicators. [ABSTRACT FROM AUTHOR]

This paper focuses on the distributed online optimization problem in multi-agent systems considering privacy preservation. Each agent exchanges local information with neighboring agents on the strongly connected time-varying directed graphs. Since the process of information transmission is prone to information leakage, a distributed push-sum dual averaging algorithm based on the differential privacy mechanism is proposed to protect the privacy of the data. In addition, to handle situations where the gradient information of the node cost function is unknown, the one-point gradient estimation is designed to calculate the true gradient information and guide the update of the decision variables. With the appropriate choice of the stepsizes and the exploration parameters, the algorithm can effectively protect the privacy of agents while achieving sublinear regret with the convergence rate O (T 3 4 ). Furthermore, this paper also explores the effect of one-point estimation parameters on the regret in the online setting and investigates the relation between the convergence effect of individual regret and differential privacy levels. Finally, several federated learning experiments were conducted to verify the efficacy of the algorithm. [ABSTRACT FROM AUTHOR]

In this paper, for the multi-agent system, the Nash equilibrium (NE) search problem for non-cooperative game with state constraints under false data injection (FDI) attack is studied. The FDI attack can directly destroy the connectivity between agents, resulting in the performance degradation or even failure for most NE search algorithms. We propose a new distributed NE search method to improve the performance of NE algorithms under FDI attacks. The NE algorithm is designed to find the solution of NE under network attack and make the system recover after the attack. However, most of the existing results only studied the NE algorithm of the non-attacking system, and the existing results rarely take into account whether the system state exceeds the safety limit, which can cause the system to crash. This paper solves the state constraints problem of the multi-agent game under the FDI attack. Finally, the reliability of the algorithm is verified by a numerical result. [ABSTRACT FROM AUTHOR]

This paper studies the fixed-time containment of the second-order nonlinear multi-agent system (MAS) accompanied by switching topologies and event-triggered communication. The agent is subjected to unknown nonlinear dynamics. A fixed-time RBF observer was constructed based on information obtained from neural networks and event-triggered communication. By combining the controller with the identification information from the observer, it is demonstrated that the system can achieve practical fixed-time output feedback containment and exclude Zeno behavior during the control process. The effectiveness of the proposed event-triggered control method for fixed-time output feedback containment control of the second-order nonlinear MAS is verified by simulation examples. [ABSTRACT FROM AUTHOR]

Distributed optimization, combining cooperative control and optimization objectives, is vital for practical applications. While current research predominantly focuses on linear multi-agent systems, the real-world demands often involve nonlinear systems with finite or fixed time constraints. This paper addresses the finite-time/fixed-time distributed optimization for nonlinear multi-agent systems with time-varying cost function. Under appropriate assumptions, we propose a finite-time distributed protocol and a fixed-time distributed protocol for the nonlinear multi-agent systems to ensure all agents achieve consensus and minimize the time-varying cost function, relaxing the conditions for strong convexity and bounded gradient difference of the cost function. Simulation experiments validate the effectiveness of these distributed protocols. [ABSTRACT FROM AUTHOR]

The bumpless transfer consensus control problem for linear homogeneous multi-agent systems subject to agent-dependent switching directed communication topologies is investigated in this paper. According to the information of graph Laplacian matrix and relative state of agent, we propose a novel agent-dependent switching law to guide the switching among these topologies, then the leader-following consensus performance of multi-agent systems is achieved via using the multiple Lyapunov functions method. Further, since the switching consensus controllers are considered, the control signal bumps are inevitable at switching instants, and some sufficient conditions via linear matrix inequalities are developed to pursue the bumpless transfer performance of multi-agent systems. Besides, the agent-dependent switching law also allows the error dynamics under each directed subtopology to be unstabilizable. Finally, the theoretical results are verified by two illustrative examples. [ABSTRACT FROM AUTHOR]

This paper addresses the event-triggered global consensus issue of second-order multi-agent systems (MASs) with asymmetric input saturation, where the zero saturation bounds are allowed. First, for the leaderless situation, we propose an event-triggered mechanism and give the criterion for realizing global consensus. Different from the traditional event-triggered strategy in an effort to exclude the Zeno behavior, a preset minimum triggering interval is introduced. That is, the control input will not be updated within this interval after the latest trigger time, and the event-triggered condition is activated after this interval. Moreover, the above results are extended to the leader–follower case. Finally, some numerical examples illustrate the effectiveness of the developed schemes. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the leader-following guaranteed performance consensus problem for multi-agent systems(MASs) controlled by event-triggered under external disturbances. First, a disturbance observer is designed for each follower, which can be used to efficiently estimate external disturbances. Second, to reduce the waste of communication resources, a new distributed event-triggered strategy based on the state estimation of neighboring agents is presented, which does not need continuous communication among agents. And the growing estimation error is reset by communication updates. The analysis illustrates that Zeno behavior can be effectively averted by formulating a lower bound on the number of normals for the minimum inter-event interval. Also, based on the above proposed state feedback consensus protocol with guaranteed performance, sufficient conditions are derived to guarantee that a MASs can achieve leader-following consensus. In addition, the consensus criterion with guaranteed performance is put forward in the form of a linear matrix inequality. The cost of guaranteed performance with leader-following structural properties is also established. At last, an example of numerical simulation is presented to confirm the derived analytical solution. [ABSTRACT FROM AUTHOR]

Consensus control in multi-agent systems (MASs) has wide-ranging applications in various domains. As the scope of applications continues to expand, ensuring the secure control of these systems to counter a diverse range of network attacks becomes highly necessary. Among these threats, Denial of Service (DoS) attacks have emerged as a major network security threat, capable of rendering targeted agents or networks unable to provide normal services. This paper presents an effective control protocol aiming to achieve leader-following consensus in a second-order MAS with event-triggered control mechanism and nonlinear dynamics under DoS attacks. The protocol utilizes absolute velocity and relative position measurements. The maximum attack frequency and duration of the DoS attacks have been obtained. Furthermore, the possibility of Zeno behavior is eliminated. Theoretical analysis demonstrates that, even under DoS attacks, consensus can be maintained among the leaders and followers within the MASs. In conclusion, the effectiveness of the proposed distributed security control protocol is validated through a case study involving a multi-vehicle cooperative system with unmanned cars. [ABSTRACT FROM AUTHOR]

This paper investigates the flocking control issue of multi-agent systems, where each agent utilizes the broadcasting communication manner and takes the Cucker–Smale style dynamic model. In the setting of broadcasting scenario, each agent broadcasts the state information only at certain moments determined by its own clock, and recalculates the control input only when its clock ticks or it receives information from the neighbors. In the Cucker–Smale model, a nonlinear weight function about the communication distance is set to portray the mutual influence degree between agents. With the help of the properties of sub-stochastic matrix, a comprehensive analysis of the asymptotic convergence of the model is performed and the algebraic conditions for achieving flocking control are established. In addition, the obtained theoretical results are further extended to the bipartite flocking control issue for multi-agent systems with both cooperative and competitive interactions. At last, numerical simulations are provided to verify the theoretical results. [ABSTRACT FROM AUTHOR]

This paper investigates the enclosing control of hybrid multi-agent systems under directed networks. Firstly, we establish some criteria for continuous-time and discrete-time multi-agent systems to achieve enclosing control. Secondly, according to the communication modes among agents, four distributed enclosing control protocols are proposed for hybrid multi-agent systems. Then, under the proposed protocols, we give the corresponding sufficient conditions to guarantee enclosing control. Finally, the correctness of our results is verified by simulations. [ABSTRACT FROM AUTHOR]

In this paper, a distributed economic dispatch algorithm based on event-triggered and fixed-time consensus is proposed for optimal dispatching among generators in smart grid. Aiming to quickly achieve economic dispatch in distributed smart grid and significantly reduce the frequency of communication between generators, the algorithm can address the supply–demand balance between the generation side and the consumption side, as well as the capacity constraints of the generators. Different from the relevant work, the proposed incremental cost can converge in fixed-time and the settling time is independent of the initial state of the generators. It will provide more flexibility for the system. Meanwhile, a fully distributed event-triggered strategy is adopted, which can reduce the interactive information between generators and avoid the waste of communication resources. Furthermore, the proposed algorithm is robust to the time-varying communication network topology. Finally, several examples are presented that validate the effectiveness of the algorithm. [ABSTRACT FROM AUTHOR]

A well-known drawback in distributed average consensus of multi-agent systems is that the exchanged information is usually delayed due to the time elapsed during the data transmission process. Using classical dynamic average consensus, delays may lead to poor performance or even instability. In this paper, we propose a novel dynamic consensus method that counteracts the negative effects of delays by means of delay compensation techniques. The interest of our dynamic consensus method with delay compensation is that it converges under mild conditions on graph connectivity and bounded reference signals, no matter how large the delays are, as long as delays are fixed and known. We also provide a formal characterization of the convergence speed of our method. Additionally, our results apply to fixed directed strongly connected, and undirected topologies. • We propose a dynamic consensus method for discrete-time systems. • We include a predictor feedback strategy for delay compensation. • Our results apply to fixed directed graphs that are strongly connected. • These results rely on a thorough eigenvalue-based analysis. • We propose parameter tuning rules aimed at improving the speed of convergence. [ABSTRACT FROM AUTHOR]

This paper explores the problem of distributed cooperative tracking control for networked nonlinear multi-agent systems (MASs) with communication delays. The difficulty of distributed control of subsystems across several geographic areas is addressed by utilizing MASs in this study. To overcome modeling difficulties, a model-free control algorithm is employed. To handle networked delay, a network predictive control approach is utilized. To address these issues in a unified manner, a novel distributed model-free integral sliding mode predictive control strategy is proposed. This approach requires simple data to make predictions to achieve distributed tracking performance while also actively compensating for delays. The effectiveness of the proposed method is demonstrated through simulations and experimental results. [ABSTRACT FROM AUTHOR]

This paper investigates the fully distributed consensus control problem for general linear multi-agent systems via dynamic event-triggered scheme. To address the need to reduce network communication burdens and avoid involving any global features of multi-agent networks, a novel fully distributed controller based on the open-loop state estimator of agents is presented. To improve anti-interference ability and practicability of the proposed approach, an event-triggered strategy which can guarantee a precise lower bound of triggering intervals for each follower is designed with a virtual internal variable. Then, the stability of the multi-agent systems is analyzed without any global network information. Several simulation experiments are conducted to illustrate theoretical results. [ABSTRACT FROM AUTHOR]

This paper proposes optimal bipartite consensus issue for discrete-time multi-agent system (DTMAS) using event-triggered control (ETC) and quantized event-triggered control (QETC). Firstly, a novel event-triggered control strategy is introduced along with specific conditions to ensure the stability for DTMAS. Due to the intractability of the Hamilton–Jacobi–Bellman (HJB) equation, through two neural networks (NNs), the value function and optimal control are approximated by the adaptive dynamic programming (ADP) method. The weight matrix of the action neural network is updated only when triggered, while also taking into account the quantization effect of the information. The stability of the weights errors and the convergence of the system dynamic are demonstrated using Lyapunov stability theory. Finally, the practicality of the improved method is confirmed a numerical example. [ABSTRACT FROM AUTHOR]