From Batch-to-Batch to online learning control: experimental motion control case study

Noud Mooren (Corresponding author), Gert Witvoet (Corresponding author), Tom Oomen (Corresponding author)

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Data-driven feedforward control can significantly improve the positioning performance of motion systems. The aim of this paper is to exploit the concept of batch-to-batch learning control with basis function, applied in an online fashion. This enables learning within a task while maintaining task flexibility. A recursive least squares optimization is proposed on the basis of input/output data to compute the optimal feedforward parameters. The proposed method is successfully validated in simulation, and applied to a benchmark motion system leading to a major performance improvement compared to only feedback control.
Originele taal-2Engels
Pagina's (van-tot)406-411
Aantal pagina's6
TijdschriftIFAC-PapersOnLine
Volume52
Nummer van het tijdschrift15
DOI's
StatusGepubliceerd - sep 2019
Evenement8th IFAC Symposium on Mechatronic Systems, MECHATRONICS 2019 - Vienna, Oostenrijk
Duur: 4 sep 20196 sep 2019

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