Finite-time consensus of multi-agent systems via event-triggered control

Abstract

This paper deals with the practical finite-time consensus for multi-agent systems (MASs) with unknown nonlinear dynamics via event-triggered control strategy. Practical finite-time consensus are achieved by an adaptive distributed control. Neural networks are employed to compensate for the nonlinear dynamics of agents. Based on Lyapunov stability theory, analysis is led on stability. In addition, it is proven that Zeno behavior is ruled out. Eventually, simulation results for consensus of a team of four agents evaluate the performance of the proposed control scheme.