Data-driven sampled-data LQR : Certainty-equivalence control via lifted cost and Riccati analysis
Gerdpratoom, Nuthasith ; Rantzer, Anders LU
and Yamamoto, Kaoru
LU
(2026)
In Systems and Control Letters
213.
- Abstract
This letter analyzes certainty-equivalence adaptive controllers for sampled-data systems through a data-driven Riccati equation. Extending a recent framework for data-driven adaptive control, the proposed formulation provides the sampled-data counterpart that explicitly accounts for intersample behavior via lifted cost representations. Sufficient conditions are derived to guarantee stability and robustness of the closed-loop system without explicit model knowledge. Furthermore, it is shown that the closed-loop performance approaches that of the model-based sampled-data LQR when a sufficiently rich data set is available.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1e32f53e-36d0-4039-9aae-fbca42ae765d
- author
- Gerdpratoom, Nuthasith
; Rantzer, Anders
LU
and Yamamoto, Kaoru
LU
- organization
- publishing date
- 2026-06
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Certainty-equivalence control, Data-driven control, Intersample dynamics, Sampled-data systems
- in
- Systems and Control Letters
- volume
- 213
- article number
- 106435
- publisher
- Elsevier
- external identifiers
-
- scopus:105035690959
- ISSN
- 0167-6911
- DOI
- 10.1016/j.sysconle.2026.106435
- language
- English
- LU publication?
- yes
- id
- 1e32f53e-36d0-4039-9aae-fbca42ae765d
- date added to LUP
- 2026-05-20 15:01:41
- date last changed
- 2026-05-20 15:02:43
@article{1e32f53e-36d0-4039-9aae-fbca42ae765d,
abstract = {{<p>This letter analyzes certainty-equivalence adaptive controllers for sampled-data systems through a data-driven Riccati equation. Extending a recent framework for data-driven adaptive control, the proposed formulation provides the sampled-data counterpart that explicitly accounts for intersample behavior via lifted cost representations. Sufficient conditions are derived to guarantee stability and robustness of the closed-loop system without explicit model knowledge. Furthermore, it is shown that the closed-loop performance approaches that of the model-based sampled-data LQR when a sufficiently rich data set is available.</p>}},
author = {{Gerdpratoom, Nuthasith and Rantzer, Anders and Yamamoto, Kaoru}},
issn = {{0167-6911}},
keywords = {{Certainty-equivalence control; Data-driven control; Intersample dynamics; Sampled-data systems}},
language = {{eng}},
publisher = {{Elsevier}},
series = {{Systems and Control Letters}},
title = {{Data-driven sampled-data LQR : Certainty-equivalence control via lifted cost and Riccati analysis}},
url = {{http://dx.doi.org/10.1016/j.sysconle.2026.106435}},
doi = {{10.1016/j.sysconle.2026.106435}},
volume = {{213}},
year = {{2026}},
}