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Bibliographic Details
Main Authors: Wolff, Tobias M., Lopez, Victor G., Müller, Matthias A.
Format: Preprint
Published: 2022
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Online Access:https://arxiv.org/abs/2210.09017
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author Wolff, Tobias M.
Lopez, Victor G.
Müller, Matthias A.
author_facet Wolff, Tobias M.
Lopez, Victor G.
Müller, Matthias A.
contents In this paper, a robust data-driven moving horizon estimation (MHE) scheme for linear time-invariant discrete-time systems is introduced. The scheme solely relies on offline collected data without employing any system identification step. We prove practical robust exponential stability for the setting where both the online measurements and the offline collected data are corrupted by non-vanishing and bounded noise. The behavior of the novel robust data-driven MHE scheme is illustrated by means of simulation examples and compared to a standard model-based MHE scheme, where the model is identified using the same offline data as for the data-driven MHE scheme.
format Preprint
id arxiv_https___arxiv_org_abs_2210_09017
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Robust Data-Driven Moving Horizon Estimation for Linear Discrete-Time Systems
Wolff, Tobias M.
Lopez, Victor G.
Müller, Matthias A.
Systems and Control
In this paper, a robust data-driven moving horizon estimation (MHE) scheme for linear time-invariant discrete-time systems is introduced. The scheme solely relies on offline collected data without employing any system identification step. We prove practical robust exponential stability for the setting where both the online measurements and the offline collected data are corrupted by non-vanishing and bounded noise. The behavior of the novel robust data-driven MHE scheme is illustrated by means of simulation examples and compared to a standard model-based MHE scheme, where the model is identified using the same offline data as for the data-driven MHE scheme.
title Robust Data-Driven Moving Horizon Estimation for Linear Discrete-Time Systems
topic Systems and Control
url https://arxiv.org/abs/2210.09017