Dual-channel dynamic event-triggered iterative learning control for nonlinear multi-agent formation control under switching topologies

This paper addresses the problems of high computational burden and excessive communication resource consumption in formation control of a class of nonlinear multi-agent systems subject to switching communication topologies, and proposes a dual-channel dynamic event-triggered iterative learning control algorithm. First, the formation tracking error is defined based on the switching topology, and a dynamic event-triggered mechanism is developed for both the sensor–controller and controller–actuator channels. Based on this, a distributed iterative learning formation control law is presented. Then, the dynamic evolution of the tracking error is formulated, and the contraction mapping principle is employed to prove convergence of the tracking error under arbitrary switching topologies. Finally, simulation results confirm the effectiveness of the proposed algorithm under switching topologies.