Iterative learning control design with high-order internal model for time-delay discrete singular multi-agent systems

In this paper, we address the problem of iterative learning control (ILC) for discrete singular multi-agent systems (MASs) with time delays, where the desired trajectories vary across iterations and are modeled by a high-order internal model (HOIM). By exploiting the equivalent constraint decomposition form of the singular system, we extend and apply a P-type ILC algorithm based on HOIM to achieve consensus control for time-delay discrete singular MASs with iteration-dependent desired trajectories. We derive convergence conditions for the proposed approach, and theoretical analysis demonstrates that the output of the singular MASs successfully achieves complete consensus tracking of the iteration-varying desired trajectories. Finally, a numerical example is provided to validate both the correctness of the primary results and the efficacy of the proposed methodology.