Adaptive iterative learning control for coordination of second-order multi-agent systems

摘要

In this paper, an efficient framework is proposed to the consensus and formation control of distributed multiagent systems with second-order dynamics and unknown time-varying parameters, by means of an adaptive iterative learning control approach. Under the assumption that the acceleration of the leader is unknown to any follower agents, a new adaptive auxiliary control and the distributed adaptive iterative learning protocols are designed. Then, all follower agents track the leader uniformly on [0, T] for consensus problem and keep the desired distance from the leader and achieve velocity consensus uniformly on [0, T] for the formation problem, respectively. The distributed multi-agent coordinations performance is analyzed based on the Lyapunov stability theory. Finally, simulation examples are given to illustrate the effectiveness of the proposed protocols in this paper.