This paper investigates fixed-time consensus (FXTC) for second-order nonlinear multi-agent systems under denial of service (DoS) attacks using event-triggered control. First, consensus in second-order nonlinear multi-agent systems with directed topologies is studied under a static event-triggered mechanism. Building upon this, dynamic auxiliary variables are introduced, and a dynamic event-triggered mechanism is designed. Consensus control protocols are proposed for both leader-follower and leaderless scenarios. Using Lyapunov stability theory and algebraic graph theory, the fixed-time consensus of multi-agent systems with directed topologies under DoS attacks is analyzed. Furthermore, Zeno behavior is excluded. Finally, numerical examples are presented to validate the theoretical results.

This paper investigates the fixed-time consensus control problem for strict-feedback multi-agent systems based on reinforcement learning. First, under the observer–critic–actor framework, neural networks are applied to the observer to address the issue of unmeasurable system states and nonlinear functions. Furthermore, based on the backstepping method, a reinforcement learning algorithm is constructed to obtain the optimal control input, which is then evaluated and optimized by the critic–actor network to derive an approximate optimal control input. Second, by constructing a Lyapunov function and utilizing the boundedness of the critic–actor network matrix trace along with Lyapunov stability theory, the fixed-time consensus of the system is proven. Finally, the effectiveness of the algorithm is verified through numerical simulations.

This paper addresses the problem of proportional consensus for multi-agent systems (MASs) under input constraints in adversarial network environments. A dynamic event-triggered proportional consensus control algorithm based on distributed observers was proposed. An input constraint mechanism was introduced to model actuator limitations, reflecting practical applications and ensuring reliable agent operation. On this basis, a dynamic event-triggered scheme was designed to significantly reduce communication load, improve resource utilization, and enhance resilience against denial-of-service (DoS) attacks. Leveraging fully distributed observers, each agent achieved proportional consensus using only local information. Theoretical analysis based on Lyapunov stability theory and graph theory provided sufficient conditions for achieving proportional consensus under DoS attacks, offering rigorous support for the method's feasibility. Simulation results demonstrated that the proposed approach effectively achieves proportional consensus for MASs under dual constraints of input saturation and adversarial attacks, while avoiding Zeno behavior.