An Iterative Learning Control Approach for Synchronization of Multi-agent Systems under Iteration-varying Graph

In this work, an iterative learning control (ILC) strategy is applied to synchronize the outputs from a group of homogeneous agents under iteration-varying communication topology. First, we show that the ILC strategy works for fixed strongly connected graph, which lays out the analysis framework for the rest developments. Next, the result is extended to iteration-varying topology, where the graph is strongly connected in each iteration. Then, the result is further generalized to uniformly strongly connected graph along the iteration domain. Matrix norm properties together with contraction mapping based analysis are utilized to prove the results. Finally, a numerical example is presented to verify the obtained results.