A Stochastic Fundamental Lemma with Reduced Disturbance Data Requirements

Fuente: arXiv
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Autores principales: Ou, Ruchuan, Pan, Guanru, Faulwasser, Timm
Formato: Preprint
Publicado: 2025
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author Ou, Ruchuan
Pan, Guanru
Faulwasser, Timm
author_facet Ou, Ruchuan
Pan, Guanru
Faulwasser, Timm
contents Recently, the fundamental lemma by Willems et al. has been extended towards stochastic LTI systems subject to process disturbances. Using this lemma requires previously recorded data of inputs, outputs, and disturbances. In this paper, we exploit causality concepts of stochastic control to propose a variant of the stochastic fundamental lemma that does not require past disturbance data in the Hankel matrices. Our developments rely on polynomial chaos expansions and on the knowledge of the disturbance distribution. Similar to our previous results, the proposed variant of the fundamental lemma allows to predict future input-output trajectories of stochastic LTI systems. We draw upon a numerical example to illustrate the proposed variant in data-driven control context.
format Preprint
id arxiv_https___arxiv_org_abs_2502_09131
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A Stochastic Fundamental Lemma with Reduced Disturbance Data Requirements
Ou, Ruchuan
Pan, Guanru
Faulwasser, Timm
Systems and Control
Optimization and Control
Recently, the fundamental lemma by Willems et al. has been extended towards stochastic LTI systems subject to process disturbances. Using this lemma requires previously recorded data of inputs, outputs, and disturbances. In this paper, we exploit causality concepts of stochastic control to propose a variant of the stochastic fundamental lemma that does not require past disturbance data in the Hankel matrices. Our developments rely on polynomial chaos expansions and on the knowledge of the disturbance distribution. Similar to our previous results, the proposed variant of the fundamental lemma allows to predict future input-output trajectories of stochastic LTI systems. We draw upon a numerical example to illustrate the proposed variant in data-driven control context.
title A Stochastic Fundamental Lemma with Reduced Disturbance Data Requirements
topic Systems and Control
Optimization and Control
url https://arxiv.org/abs/2502.09131