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.

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.