Leader-following consensus of multi-agent systems with uncertain weight coupling topological graph using distributed adaptive iterative learning control

In this paper, the distributed leader-following consensus problem of multi-agent systems with uncertain topological graph is formulated from the viewpoint of two dimensional systems over a finite time interval. Combining with iterative learning control, the fully distributed consensus protocols with the adaptive updating laws of unknown time-varying coupling strengthes appeared in the communication topology are proposed for linear multi-agent systems. By choosing appropriate Lyapunov-Krasovskii functional, the leader-following consensus can be achieved on [0,T] for all undirected connected topology graph when the number of iterations tends to infinity. Finally, a simulation example is given to demonstrate the effectiveness of theoretical results.