Data-Driven Output-Based Approach to the Output Regulation Problem of Unknown Linear Systems via Value Iteration

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Main Authors:	Lin, Haoyan, Huang, Jie
Format:	Preprint
Published:	2026
Subjects:	Optimization and Control
Online Access:	Acceder al recurso
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author	Lin, Haoyan Huang, Jie
author_facet	Lin, Haoyan Huang, Jie
contents	The output regulation problem for unknown linear systems has been studied using state-based and output-based internal model approaches in the special case with no disturbances. This paper further investigates the output regulation problem for unknown linear systems using a data-driven output-based approach via value iteration. For this purpose, we first develop a novel output-feedback control law that does not explicitly rely on the observer gain to solve the output regulation problem. We then show that the data-driven approach for designing an output-feedback control law for the given plant can be reduced to the data-driven design of a state-feedback control law for a well-defined augmented auxiliary system. As a result, we develop a systematic data-driven approach to solve the output regulation problem for unknown linear systems via value iteration. Finally, we establish a relation between the data-driven state-feedback control law and the data-driven output-feedback control law in the LQR sense.
format	Preprint
id	arxiv_https___arxiv_org_abs_2601_02748
institution	arXiv
publishDate	2026
record_format	arxiv
spellingShingle	Data-Driven Output-Based Approach to the Output Regulation Problem of Unknown Linear Systems via Value Iteration Lin, Haoyan Huang, Jie Optimization and Control The output regulation problem for unknown linear systems has been studied using state-based and output-based internal model approaches in the special case with no disturbances. This paper further investigates the output regulation problem for unknown linear systems using a data-driven output-based approach via value iteration. For this purpose, we first develop a novel output-feedback control law that does not explicitly rely on the observer gain to solve the output regulation problem. We then show that the data-driven approach for designing an output-feedback control law for the given plant can be reduced to the data-driven design of a state-feedback control law for a well-defined augmented auxiliary system. As a result, we develop a systematic data-driven approach to solve the output regulation problem for unknown linear systems via value iteration. Finally, we establish a relation between the data-driven state-feedback control law and the data-driven output-feedback control law in the LQR sense.
title	Data-Driven Output-Based Approach to the Output Regulation Problem of Unknown Linear Systems via Value Iteration
topic	Optimization and Control
url	https://arxiv.org/abs/2601.02748

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