Event-triggered proportional consensus with input constraints in adversarial networks

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.