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

Abstract

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 OE0, T for consensus problem and keep the desired distance from the leader and achieve velocity consensus uniformly on OE0, 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.

Distributed adaptive repetitive consensus control framework for uncertain nonlinear leader–follower multi-agent systems

“…Remark 1: In the literatures [31][32][33], the multi-agent systems should operate repetitively over a fixed time interval. Being different with [31][32][33], in this paper, the dynamic of each follower has parametric uncertainty. Then, to reject the parametric uncertainty, we should combine the distributed consensus problem by means of repetitive control method to investigate the asymptotic consensus.…”

“…The paper [32] also addressed an adaptive iterative learning control for multi-agent systems consensus tracking under repeatable control environment, where the agent dynamics were assumed to be inherently nonlinear with unknown time-varying parameters. Further, in [33], the authors extended the results in [31] to second-order multi-agent systems by means of an adaptive ILC approach.…”

“…To solve the consensus problem of the multi-agent systems with time-varying parametric uncertainties, much attention has been focused on the study of multi-agent systems by using adaptive iterative learning control [31][32][33]. In [31], a distributed adaptive iterative learning control was presented for the consensus problem of leader-following multi-agent systems, and the dynamic of each follower agent was nonlinear and with unknown time-varying parameter.…”

“…Repetitive control is mainly used in continuous processes for tracking or rejecting periodic exogenous signals. The existing methods in [31][32][33] solved the coordination problems for the finite interval by using ILC method. How to investigate the asymptotic consensus for multi-agent systems with unknown time-varying parameters by means of repetitive control approach, which is still an open problem and remains unsolved.…”

Formation-containment control for second-order multi-agent systems with time-varying delays

“…A formation control approach for second-order multi-agent systems with time-varying delays was presented in [14]. In [15], an adaptive iterative learning based formation control method was proposed for second-order multi-agent systems. A hybrid consensus-based formation control method was presented for second-order multi-agent systems to achieve desired formation in [16].…”