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Auteurs principaux: Nauta, Talitha, Pates, Richard
Format: Preprint
Publié: 2026
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Accès en ligne:https://arxiv.org/abs/2603.05239
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author Nauta, Talitha
Pates, Richard
author_facet Nauta, Talitha
Pates, Richard
contents Graphical methods for system analysis have played a central role in control theory. A recently emerging tool in this field is the Scaled Relative Graph (SRG). In this paper, we further extend its applicability by showing how the SRG of discrete-time linear-time-invariant (LTI) systems can be computed exactly from its state-space representation using linear matrix inequalities. We additionally propose a fully data-driven approach where we demonstrate how to compute the SRG exclusively from input-output data. Furthermore, we introduce a robust version of the SRG, which can be computed from noisy data trajectories and contains the SRG of the actual system.
format Preprint
id arxiv_https___arxiv_org_abs_2603_05239
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Computing Scaled Relative Graphs of Discrete-time LTI Systems from Data
Nauta, Talitha
Pates, Richard
Systems and Control
Optimization and Control
Primary 47A05, 51M15, Secondary 47A12
Graphical methods for system analysis have played a central role in control theory. A recently emerging tool in this field is the Scaled Relative Graph (SRG). In this paper, we further extend its applicability by showing how the SRG of discrete-time linear-time-invariant (LTI) systems can be computed exactly from its state-space representation using linear matrix inequalities. We additionally propose a fully data-driven approach where we demonstrate how to compute the SRG exclusively from input-output data. Furthermore, we introduce a robust version of the SRG, which can be computed from noisy data trajectories and contains the SRG of the actual system.
title Computing Scaled Relative Graphs of Discrete-time LTI Systems from Data
topic Systems and Control
Optimization and Control
Primary 47A05, 51M15, Secondary 47A12
url https://arxiv.org/abs/2603.05239