TY - JOUR
T1 - Gaussian Processes for Advanced Motion Control
AU - Poot, M.M.
AU - Portegies, Jim
AU - Mooren, Noud
AU - van Haren, Max
AU - van Meer, Max
AU - Oomen, Tom
PY - 2022
Y1 - 2022
N2 - Machine learning techniques, including Gaussian processes (GPs), are expected to play a significant role in meeting speed, accuracy, and functionality requirements in future data-intensive mechatronic systems. This paper aims to reveal the potential of GPs for motion control applications. Successful applications of GPs for feedforward and learning control, including the identification and learning for noncausal feedforward, position-dependent snap feedforward, nonlinear feedforward, and GP-based spatial repetitive control, are outlined. Experimental results on various systems, including a desktop printer, wirebonder, and substrate carrier, confirmed that data-based learning using GPs can significantly improve the accuracy of mechatronic systems.
AB - Machine learning techniques, including Gaussian processes (GPs), are expected to play a significant role in meeting speed, accuracy, and functionality requirements in future data-intensive mechatronic systems. This paper aims to reveal the potential of GPs for motion control applications. Successful applications of GPs for feedforward and learning control, including the identification and learning for noncausal feedforward, position-dependent snap feedforward, nonlinear feedforward, and GP-based spatial repetitive control, are outlined. Experimental results on various systems, including a desktop printer, wirebonder, and substrate carrier, confirmed that data-based learning using GPs can significantly improve the accuracy of mechatronic systems.
KW - feedforward control
KW - gaussian processes
KW - learning control
UR - http://www.scopus.com/inward/record.url?scp=85130095439&partnerID=8YFLogxK
U2 - 10.1541/ieejjia.21011492
DO - 10.1541/ieejjia.21011492
M3 - Article
SN - 2187-1094
VL - 11
SP - 396
EP - 407
JO - IEEJ Journal of Industry Applications
JF - IEEJ Journal of Industry Applications
IS - 3
M1 - 21011492
ER -