On-line instrumental variable-based feedforward tuning for non-resetting motion tasks
Noud Mooren (Eindhoven University of Technology)
Gert Witvoet (TNO, Eindhoven University of Technology)
Tom Oomen (TU Delft - Team Jan-Willem van Wingerden, Eindhoven University of Technology)
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Abstract
Data-driven feedforward control for tracking of varying and non-resetting point-to-point references requires continuous updating of feedforward parameters instead of task-by-task updating. The aim of this paper is to develop an adaptive feedforward controller for non-resetting point-to-point motion tasks by a data-driven feedforward controller. An approximate optimal instrumental variable (IV) estimator with real-time bootstrapping is employed in a closed-loop setting to update the feedforward parameters. A case study on a wafer-stage and experimental validation on a benchmark motion system show the performance benefit.
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