A Dynamic Event-Triggered Transmission Strategy for Distributed Convex Optimization

A dynamic event-triggered transmission strategy is considered for the continuous-time distributed convex optimization algorithm over a strongly connected and weight-balanced directed graph. An auxiliary variable is introduced in the dynamic event-triggered control (DETC) that is free of Zeno phenomenon. We model the DETC system into a hybrid system. Using Lyapunov stability theory, we give a detailed proof for convergence of the continuous-time distributed convex optimization algorithm. Finally, a numerical simulation shows that the DETC can effectively save network communication resources compared with a static event-triggered control (SETC).