In this paper, the iterative learning control technique is applied for singular multi-agent systems to perform consensus tracking. Here, the communication among the followers is described by a directed graph, and only a portion of the followers can receive the leader’s information. Based on the equivalent restrict decomposition form of singular agents, a unified distributed learning algorithm is proposed in both continuous-time domain and discrete-time domain. Furthermore, the convergence condition of the algorithm is presented and analyzed. It is shown that the algorithm can guarantee the states of the followers converge to the leader’s trajectory on a finite time interval along the iteration axis. Finally, two simulation examples are given to illustrate the effectiveness of the theoretical results.

中文翻译：

---

基于迭代学习方法的奇异多智能体系统的共识控制

本文将迭代学习控制技术应用于奇异多智能体系统中，以进行共识跟踪。在此，跟随者之间的通信由有向图描述，只有一部分跟随者可以接收领导者的信息。基于奇异主体的等效限制分解形式，提出了一种连续时间域和离散时间域的统一分布式学习算法。并给出了算法的收敛条件。结果表明，该算法可以保证跟随者的状态沿着迭代轴在有限的时间间隔上收敛到领导者的轨迹。最后，给出了两个仿真例子来说明理论结果的有效性。