There is a newer version of this record available.

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 Yan

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.

Files (1.4 MB)
Name Size
1.4 MB Download
All versions This version
Views 406313
Downloads 282216
Data volume 391.3 MB300.2 MB
Unique views 357284
Unique downloads 253196


Cite as