Preprint Open Access
Gaussian Process Position-Dependent Feedforward: With Application to a Wire Bonder
Max van Haren; Maurice Poot; Dragan Kostić; Robin van Es; Jim Portegies; Tom Oomen
Data collector(s)
Kelvin Kai Wa YanMechatronic 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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- Publication date:
- December 16, 2021
- DOI:
-
- Keyword(s):
- Mechatronic Systems Feedforward Control Gaussian Processes
- Communities:
- License (for files):
- Creative Commons Attribution 4.0 International