Distributed adaptive iterative learning control for 2D multi agent systems

Abstract

This letter addresses the output consensus problem for a class of two‐dimensional (2D) multi agent systems (MASs) described by Fornasini–Marchesini model. By transforming the 2D agent into a compact form, an adaptive variable, which adjusted by the tracking errors of itself and the neighbour agents, is designed to approximate the unknown varying coefficient. Then, based on the approximated coefficient and the iteration‐varying reference surfaces, the distributed adaptive iterative learning control strategy is obtained. The output consensus of the 2D multi agent is proved. Simulations are included to verify the effectiveness of the investigated distributed adaptive ILC for 2D MASs with random variations on initial condition and reference surface.