Nonlinear Repetitive Control for Mitigating Noise Amplification
Leontine Aarnoudse (Eindhoven University of Technology)
Alexey Pavlov (Norwegian University of Science and Technology (NTNU))
Johan Kon (Eindhoven University of Technology)
Tom Oomen (TU Delft - Team Jan-Willem van Wingerden, Eindhoven University of Technology)
More Info
expand_more
Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.
Abstract
Repetitive control can lead to high performance by attenuating periodic disturbances completely, yet it may amplify non-periodic disturbances. The aim of this paper is to achieve both fast learning and low errors in repetitive control. To this end, a nonlinear learning filter is introduced that distinguishes between periodic and non-periodic errors based on their typical amplitude characteristics to adapt the extent to which they are included in the repetitive controller. Convergence conditions for the nonlinear repetitive control system are derived by casting the resulting closed-loop as a discrete-time convergent system. Simulation results of the proposed approach demonstrate fast learning and small errors.