This article studies bipartite time-varying formation-containment control (FCC) for large-scale multiagent systems (MASs) with unknown input of the leader. Large-scale systems are layered and grouped according to tasks to accomplish hierarchical bipartite time-varying FCC. It solves problems of strong coupling, communication redundancy, and collision avoidance in large-scale networks and enables many followers to implement new interactive behaviors in multiple convex hulls formed by leaders. First, for a constructed four-layer topology with group directed spanning tree, hierarchical bipartite time-varying FCC protocols with a collision avoidance term are designed to achieve collision-free bipartite group tracking control in a multiconvex hull. Then, appropriate control parameters are designed in protocols to promote effective information transmission between layers and groups. Compared with existing FCC strategies, hierarchical bipartite time-varying FCC strategies improve the control performance of MASs. Finally, the effectiveness of all protocols is proved through Lyapunov’s theorem and linear matrix inequality. The feasibility of protocols was verified through simulations.

This article addresses the tracking control issue within a prescribed-time (PT) for nonlinear multiagent systems (MASs) affected by model uncertainties and external disturbances. First, the approximation characteristics of fuzzy logic systems are employed to design corresponding adaptive fuzzy control laws, which approximate the unknown parts of the system to approximate known values. Then, by utilizing the fuzzy inputs from multiple agents and defined rules, the system adapts to external mismatched disturbances. Next, a novel time-scale function is designed as part of the controller gain. Unlike traditional gain functions, this function ensures the system achieves consensus within a predetermined time while avoiding infinite growth, thereby ensuring the boundedness of the control signals. Introducing this function into the controller, along with the adaptive fuzzy control laws and intermediate control laws, constructs an adaptive control law to achieve control over each agent and achieve PT consensus of the uncertain system. In the controller design, the complexity of proving system stability is reduced by avoiding fractional-order Lyapunov differential inequalities, and each agent has corresponding control parameters. Finally, the efficacy of the results from the theoretical analysis is confirmed by a pair of simulation examples.

This article investigates the leader-following synchronization problem of multiagent systems (MASs) under hybrid cyber attacks, which refers to deception attacks and multichannel independent denial-of-service (DoS) attacks in communication channels. In order to achieve the secure control of MASs under hybrid cyber attacks, a novel impulsive control method based on topology switching is proposed, and a new algorithm for determining impulsive instants is designed. In addition, the cooperative-competitive relationship between agents is also considered, which is more in line with reality. Sufficient conditions for ensuring secure control of MASs and a parametric upper bound on the error vector norm between the agents and the leader are obtained. Finally, the numerical simulation verified the effectiveness of the proposed algorithm.

This article is centered on the optimal consensus problem of the multiagent systems (MASs) with time delays. By designing a new augmented state, the delayed MASs are reformulated as a delay-free system, and each agent is to minimize its local cost that may depend on the decisions of the other agents, which is regarded as a Nash equilibrium problem. To this end, we propose a multiagent deterministic policy gradient (MADPG) method based on actor–critic (AC) networks to minimize the local cost ($Q$-function) by introducing the policy gradient technique, and its convergence and optimality are proven as well. In particular, we develop an optimized prioritized experience replay (PER) strategy that allows high-value samples to be selected with a higher probability, which enhance networks’ data utilization. Finally, the effectiveness of the algorithm and the advantages of PER are demonstrated with a simulated example and a comparative simulation.

This article considers distributed optimization by a group of agents over an undirected network. The objective is to minimize the sum of a twice differentiable convex function and two possibly nonsmooth convex functions, one of which is composed of a bounded linear operator. A novel distributed primal-dual fixed point algorithm is proposed based on an adapted metric method, which exploits the second-order information of the differentiable convex function. Furthermore, by incorporating a randomized coordinate activation mechanism, we propose a randomized asynchronous iterative distributed algorithm that allows each agent to randomly and independently decide whether to perform an update or remain unchanged at each iteration, and thus alleviates the communication cost. Moreover, the proposed algorithms adopt nonidentical stepsizes to endow each agent with more independence. Numerical simulation results substantiate the feasibility of the proposed algorithms and the correctness of the theoretical results.

In this article, the cluster consensus of heterogeneous multiagent systems is investigated via dynamic event-triggered and pining control strategies. Comprehensively considering the cooperative and competitive interactions among the agents, a novel cluster consensus control protocol is designed, and a class of fully distributed dynamic event-triggered laws that do not depend on the global information is proposed. Being distinct from the traditional static threshold value, a time-varying threshold value is introduced which can effectively reduce the trigger time. Meanwhile, some sufficient conditions are obtained theoretically by using Lyapunov stability theory and the pinning control strategy is addressed as well. Furthermore, it has also been shown that each agent can exclude Zeno behavior. Finally, two simulated examples are given to illustrate the correctness and validity of the proposed methods and our findings.

This article discusses the couple-group consensus for heterogeneous multiagent systems via event-triggered and pinning control methods. Considering cooperative-competitive interaction among the agents, a novel group consensus protocol is designed. As inducing the time-correlation threshold function, a class of fully distributed event-triggered conditions without depending on any global information is proposed. Utilizing the Lyapunov stability theory, some sufficient conditions are obtained. Under hybrid event triggered and pinning control, pinning control strategies are first introduced. It is shown that under the proposed strategies, all agents can asymptotically achieve pinning couple-group consensus with discontinuous communication in a fully distributed way. Furthermore, the Zeno behavior for each agent is overcome. Finally, the reduction of the systems' controller update frequency and the correctness of our conclusions are illustrated by some simulations.

In this article, we consider a class of decentralized nonsmooth composite optimization problems over undirected graphs. The global optimization problem is to minimize the sum of local objective functions consisting of a Lipschitz-differentiable convex function and two possibly nonsmooth convex functions, one of which contains a bounded linear operator. The goal is to solve the global optimization problem through decentralized computation and communication over a network of agents without a central coordinator. Through using triple proximal splitting operators to deal with the nonsmooth terms, we come up with a novel decentralized algorithm with uncoordinated stepsizes, where the stepsizes with independent upper bounds are also distributed for agents or edges over the communication network. Furthermore, we establish the sublinear convergence rate for the proposed algorithm in terms of the first-order optimality residual in a nonergodic sense. Simulation experiments on a constrained quadratic programming problem and an optimal load-sharing problem are carried out to verify the correctness of the theoretical results.

In this article, the problem of couple-group consensus for the heterogeneous multiagent systems (MASs) composed of first-order and second-order agents are investigated by hybrid pinning and adaptive control methods, respectively. A novel distributed control protocol of group consensus is proposed via the cooperative-competitive relationship between the agents. Based on algebraic graph theory, matrix analysis and Lyapunov stability theorem, the sufficient conditions and corresponding pinning strategies for the heterogeneous MASs with the weakly connected topology are obtained. In addition, we find that the value of pinning gain should meet a certain condition for guaranteeing the achievement of group consensus. Finally, the validity of our results is verified by some simulated examples.

The group consensus problems of heterogeneous multiagent networks with input time delays are investigated in this paper. In this complex networks, the agents' dynamics are modeled by the first-order and the second-order multiagent systems, where a novel dynamic group consensus protocol is designed through the competitive relationship among the agents. By using matrix theory and the frequency-domain method, some algebraic criteria are theoretically established for reaching a group consensus in the following two cases: 1) with the identical and 2) different input time delays. Meanwhile, the conservative assumptions existed in the relevant literatures are absolutely relaxed, i.e., the in-degree balance and the geometric multiplicity of zero eigenvalue of Laplacian matrix are at least two. Finally, the effectiveness of our results is illustrated by numerical examples.

In this paper, we discuss the couple-group consensus problem for heterogeneous multi-agent systems with communication and input time delays. From the perspective of the competitive relationship between agents, a novel group consensus protocol is designed which is distinctive to most of the existing works based on the cooperative networks. Specifically, we relax the restrictive assumptions existed in the related works and theoretically propose the sufficient algebraic criteria for the realization of couple-group consensus of the systems under the influence of multiple time delays. The results show that the achievement of the couple-group consensus depends on the agents' input time delays, coupling weights and the systems' control parameters, whereas it is independent of the communication time delays between the agents. Finally, the validity of our findings is verified by several simulations.

This paper is concerned with pinning consensus control problem for multi-agent networks with general connected topology which neither needs to be strongly connected nor needs to contain a directed spanning tree. By adopting adaptive control laws, some promising criteria are proposed analytically, which can guarantee the networks to achieve consensus asymptotically. Meanwhile, a novel and effective pinning scheme is addressed as well. In addition, it is interesting to find out that the rule does not always hold, that is the more nodes are pinned, the faster the network converges. Finally, the validity and correctness of our theoretical findings are verified by several numerical simulated experiments.