Functional Iterative Learning Control for Linear Systems

Many linear dynamic systems can usually be modeled in continuous time. However, to simplify the learning phase of Iterative Learning Control, the system output signal is frequently sampled, while the input is discretized, de-facto obtaining a discrete-time system. This work aims at preserving the continuous nature of the system, while tracking sampled outputs. To this end, we model the input signal as an element of a functional subspace, exploiting its infinite-dimension. Simulation results are presented.