Title
Gaussian process repetitive control: beyond periodic internal models through kernels
Author
Mooren, N.
Witvoet, G.
Oomen, T.
Publication year
2022
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.
Subject
Disturbance rejection
Gaussian processes
Internal model control
Repetitive control
High Tech Systems & Materials
Industrial Innovation
To reference this document use:
http://resolver.tudelft.nl/uuid:3a88ad2a-1e9e-4cc8-9221-d1d390dcac2f
DOI
https://doi.org/10.1016/j.automatica.2022.110273
TNO identifier
967453
Publisher
Elsevier, Amsterdam
ISSN
0005-1098
Source
Automatica, 140 (140)
Document type
article