On the role of the signature transform in nonlinear systems and data-driven control

Fuente: arXiv
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Main Authors: Scampicchio, Anna, Zeilinger, Melanie N.
Format: Preprint
Published: 2024
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author Scampicchio, Anna
Zeilinger, Melanie N.
author_facet Scampicchio, Anna
Zeilinger, Melanie N.
contents Classic control techniques typically rely on a model of the system's response to external inputs, which is difficult to obtain from first principles especially if the unknown dynamics are nonlinear. In this paper, we address this issue by presenting an approach based on the so-called signature transform, a tool that is still largely unexplored in data-driven control. We first show that the signature provides rigorous and practically effective features to represent and predict system trajectories. Furthermore, we propose a novel use of this tool on an output-matching problem, paving the way for signature-based, data-driven predictive control.
format Preprint
id arxiv_https___arxiv_org_abs_2409_05685
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle On the role of the signature transform in nonlinear systems and data-driven control
Scampicchio, Anna
Zeilinger, Melanie N.
Systems and Control
Classic control techniques typically rely on a model of the system's response to external inputs, which is difficult to obtain from first principles especially if the unknown dynamics are nonlinear. In this paper, we address this issue by presenting an approach based on the so-called signature transform, a tool that is still largely unexplored in data-driven control. We first show that the signature provides rigorous and practically effective features to represent and predict system trajectories. Furthermore, we propose a novel use of this tool on an output-matching problem, paving the way for signature-based, data-driven predictive control.
title On the role of the signature transform in nonlinear systems and data-driven control
topic Systems and Control
url https://arxiv.org/abs/2409.05685