Event-triggered consensus control of high-order multi-agent systems with arbitrary switching topologies via model partitioning approach

Abstract

This paper investigates the problem of event-triggered consensus control for high-order multi-agent systems with arbitrary switching topologies. To achieve this goal, a novel model partitioning approach is proposed, where the high-order error systems are partitioned into stable subsystems and unstable subsystems through coordinate transformations. By analyzing the unstable subsystems under arbitrary switching, an appropriate controller can be designed to guarantee the subsystems stable. Then the controller gain of the multi-agent systems can be derived through inverse transformations. The designed controller can guarantee the error state convergence under each topology within any time interval, which further ensures the consensus of high-order multi-agent systems under arbitrary switching topologies. Finally, a numerical example is provided to illustrate the feasibility of the theoretical results.