Cross-Coupled Iterative Learning Control for Complex Systems

A Monotonically Convergent and Computationally Efficient Approach

Conference paper (2022)

Authors

Leontine Aarnoudse Eindhoven University of Technology
Johan Kon Eindhoven University of Technology
Koen Classens Eindhoven University of Technology
Max Van Meer Eindhoven University of Technology
Maurice Poot Eindhoven University of Technology
Paul Tacx Eindhoven University of Technology
Nard Strijbosch IBS Precision Engineering
Tom Oomen Team Jan-Willem van Wingerden - Mechanical, Maritime and Materials Engineering , Eindhoven University of Technology
Research Group
Team Jan-Willem van Wingerden (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2022 Leontine Aarnoudse, Johan Kon, Koen Classens, Max van Meer, Maurice Poot, Paul Tacx, Nard Strijbosch, T.A.E. Oomen
DOI: https://doi.org/10.1109/CDC51059.2022.9993408
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Published Date

2022

Language

English

Reuse Rights

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Faculty

Mechanical, Maritime and Materials Engineering

Department

Delft Center for Systems and Control

Research Group

Team Jan-Willem van Wingerden

Abstract

Cross-coupled iterative learning control (ILC) can achieve high performance for manufacturing applications in which tracking a contour is essential for the quality of a product. The aim of this paper is to develop a framework for norm-optimal cross-coupled ILC that enables the use of exact contour errors that are calculated offline, and iteration-and time-varying weights. Conditions for the monotonic convergence of this iteration-varying ILC algorithm are developed. In addition, a resource-efficient implementation is proposed in which the ILC update law is reframed as a linear quadratic tracking problem, reducing the computational load significantly. The approach is illustrated on a simulation example.

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