State-tracking iterative learning control in frequency domain design for improved intersample behavior
Wataru Ohnishi (University of Tokyo)
Nard Strijbosch (Eindhoven University of Technology)
Tom Oomen (Eindhoven University of Technology, TU Delft - Team Jan-Willem van Wingerden)
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
Iterative learning control (ILC) yields perfect output-tracking performance at sampling instances for systems that perform repetitive tasks. The aim of this article is to develop a framework for a state-tracking ILC that mitigates oscillatory intersample behavior, which is often encountered in output tracking ILC. As a framework for the analysis, the stability of the iterative domain including the robustness filter and the asymptotic signal is formulated. In addition, as a framework for the design, the design method using frequency response data to reduce the modeling effort, the learning filter design based on inversion, and the specific design procedure of the robustness filter are presented. The designed method is successfully applied to a motion system and it is shown that the presented state-tracking ILC provides better intersample behavior than the standard output-tracking ILC.