Consensus tracking control via iterative learning for singular multi-agent systems

This study considers the consensus tracking problem of singular multi-agent systems by using an iterative learning control approach. 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. For such singular multi-agent systems, a unified iterative learning algorithm is proposed in both continuous-time domain and discrete-time domain. Furthermore, the convergence condition of the algorithm is presented and analysed. In this study, the main contribution is to extend the iterative learning control theory from multi-agent systems to singular multi-agent systems. It is shown that the algorithm can guarantee the outputs of the followers converge to the leader's trajectory on a finite time interval along the iteration axis. Finally, the provided examples illustrate the effectiveness of the theoretical results.