Gaussian Process Position-Dependent Feedforward: With Application to a Wire Bonder

Conference paper (2022)

Authors

Max van Haren Eindhoven University of Technology
Maurice Poot Eindhoven University of Technology
Dragan Kostic ASM Pacific Technology
Robin van Es ASM Pacific Technology
Jim Portegies Eindhoven University of Technology
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 Max van Haren, Maurice Poot, Dragan Kostic, Robin van Es, Jim Portegies, T.A.E. Oomen
DOI: https://doi.org/10.1109/AMC51637.2022.9729327
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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

Mechatronic systems have increasingly stringent performance requirements for motion control, leading to a situation where many factors, such as position-dependency, cannot be neglected in feedforward control. The aim of this paper is to compensate for position-dependent effects by modeling feedforward parameters as a function of position. A framework to model and identify feedforward parameters as a continuous function of position is developed by combining Gaussian processes and feedforward parameter learning techniques. The framework results in a fully data-driven approach, which can be readily implemented for industrial control applications. The framework is experimentally validated and shows a significant performance increase on a commercial wire bonder.

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