Event-triggered consensus of multi-agent systems with uncertain control gain via distributed fuzzy logic observer

Abstract

An event-triggered adaptive backstepping control methodology is proposed to achieve leader-following consensus of uncertain nonlinear high-order multi-agent systems with unknown control gains. In light of the partial observability limitation, adaptive distributed observers are employed to estimate the unobservable states of the leader, whereas local state observers are utilized to reconstruct the states of the followers. By integrating fuzzy logic systems, the unknown nonlinear dynamics are modeled, guaranteeing reliable state prediction in complex and partially observable scenarios. Moreover, the novel relative threshold event-triggered scheme is designed to reduce the frequency of data interactions while ensuring that the tracking error approaches near-zero. Eventually, the effectiveness and superiority of the devised controller are clearly demonstrated through comprehensive simulation results.