Wang Yi, Ma Zhongjun, Chen Guanrong
IEEE Trans Neural Netw Learn Syst. 2018 Aug;29(8):3490-3498. doi: 10.1109/TNNLS.2017.2726354. Epub 2017 Aug 11.
In order to avoid congestion in the second-order nonlinear leader-following multiagent systems over capacity-limited paths, an approach called cluster lag consensus is proposed, which means that the agents in different clusters will pass through the same positions with the same velocities but lag behind the leader at different times. Lyapunov functionals and matrix theory are applied to analyze such cluster lag consensus. It is shown that when the graphic roots of clusters are influenced by the leader and the intracoupling of cluster agents is larger than a threshold, the cluster lag consensus can be achieved. Furthermore, the cluster lag consensus with a time-varying communication topology is investigated. Finally, an illustrative example is presented to demonstrate the effectiveness of the theoretical results. In particular, when the physical sizes of the agents are taken into consideration, it is shown that with a rearrangement and a position transformation, the multiagent system will reach cluster lag consensus in the new coordinate system. This means that all agents in the same cluster will reach consensus on the velocity, but their positions may be different and yet their relative positions converge to a constant asymptotically.
为了避免二阶非线性领导者跟随多智能体系统在容量受限路径上出现拥塞，提出了一种称为簇滞后一致性的方法，这意味着不同簇中的智能体将以相同速度通过相同位置，但在不同时间落后于领导者。应用李雅普诺夫泛函和矩阵理论来分析这种簇滞后一致性。结果表明，当簇的图根受到领导者影响且簇内智能体的内部耦合大于某个阈值时，可实现簇滞后一致性。此外，还研究了具有时变通信拓扑的簇滞后一致性。最后，给出一个示例来说明理论结果的有效性。特别地，当考虑智能体的物理大小时，结果表明通过重新排列和位置变换，多智能体系统在新坐标系中将达到簇滞后一致性。这意味着同一簇中的所有智能体在速度上将达成一致，但其位置可能不同，不过它们的相对位置会渐近收敛到一个常数。
