Gaussian Process Repetitive Control for Suppressing Spatial Disturbances

TL;DR

This paper introduces a novel spatial repetitive control method using Gaussian processes to suppress position-dependent disturbances in motion systems, effectively handling a-periodic time domain disturbances.

Contribution

It develops a new spatial RC framework with GP-based memory and a periodic kernel to address a-periodic disturbances in the time domain.

Findings

Effective disturbance attenuation demonstrated in a mechatronic example.

The GP-based approach handles intermittent observations well.

The method improves disturbance suppression over traditional time-based RC.

Abstract

Motion systems are often subject to disturbances such as cogging, commutation errors, and imbalances, that vary with velocity and appear periodic in time for constant operating velocities. The aim of this paper is to develop a repetitive controller (RC) for disturbances that are not periodic in the time domain, yet occur due to an identical position-domain disturbance. A new spatial RC framework is developed, allowing to attenuate disturbances that are periodic in the position domain but manifest a-periodic in the time domain. A Gaussian process (GP) based memory is employed with a suitable periodic kernel that can effectively deal with the intermittent observations inherent to the position domain. A mechatronic example confirms the potential of the method.