Consensus tracking control via iterative learning for singular multi‐agent systems. Issue 11 (15th May 2019) - Gu, Panpan
Abstract : 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.