Iterative learning control for multi-agent systems with impulsive consensus tracking

In this paper, we adopt D-type and PD-type learning laws with the initial state of iteration to achieve uniform tracking problem multi-agent systems subjected impulsive input. For system impulse, show that all agents are driven a given asymptotical consensus as number increases via proposed if virtual leader has path any follower agent. Finally, an example is illustrated verify effectiveness by continuous or piecewise desired trajectory.