Gaussian process repetitive control: Beyond periodic internal models through kernels

Noud Mooren*, Gert Witvoet, Tom Oomen

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

5 Citations (Scopus)
52 Downloads (Pure)

Abstract

Repetitive control enables the exact compensation of periodic disturbances if the internal model is appropriately selected. The aim of this paper is to develop a novel synthesis technique for repetitive control (RC) based on a new more general internal model. By employing a Gaussian process internal model, asymptotic rejection is obtained for a wide range of disturbances through an appropriate selection of a kernel. The implementation is a simple linear time-invariant (LTI) filter that is automatically synthesized through this kernel. The result is a user-friendly design approach based on a limited number of intuitive design variables, such as smoothness and periodicity. The approach naturally extends to reject multi-period and non-periodic disturbances, exiting approaches are recovered as special cases, and a case study shows that it outperforms traditional RC in both convergence speed and steady-state error.

Original languageEnglish
Article number110273
Number of pages13
JournalAutomatica
Volume140
DOIs
Publication statusPublished - 2022

Keywords

  • Disturbance rejection
  • Gaussian processes
  • Internal model control
  • Repetitive control

Fingerprint

Dive into the research topics of 'Gaussian process repetitive control: Beyond periodic internal models through kernels'. Together they form a unique fingerprint.

Cite this