Cross-Coupled Iterative Learning Control for Complex Systems
A Monotonically Convergent and Computationally Efficient Approach
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)
T.A.E. Oomen (TU Delft - Team Jan-Willem van Wingerden, Eindhoven University of Technology)
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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.