dc.identifier.uri |
http://dx.doi.org/10.15488/15888 |
|
dc.identifier.uri |
https://www.repo.uni-hannover.de/handle/123456789/16012 |
|
dc.contributor.author |
Kohler, Matthias
|
|
dc.contributor.author |
Berberich, Julian
|
|
dc.contributor.author |
Müller, Matthias A.
|
|
dc.contributor.author |
Allgower, Frank
|
|
dc.date.accessioned |
2024-01-15T09:30:40Z |
|
dc.date.available |
2024-01-15T09:30:40Z |
|
dc.date.issued |
2022 |
|
dc.identifier.citation |
Kohler, M.; Berberich, J.; Müller, M.A.; Allgower, F.: Data-driven distributed MPC of dynamically coupled linear systems. In: IFAC-PapersOnLine 55 (2022), Nr. 30, S. 365-370. DOI: https://doi.org/10.1016/j.ifacol.2022.11.080 |
|
dc.description.abstract |
In this paper, we present a data-driven distributed model predictive control (MPC) scheme to stabilise the origin of dynamically coupled discrete-time linear systems subject to decoupled input constraints. The local optimisation problems solved by the subsystems rely on a distributed adaptation of the Fundamental Lemma by Willems et al., allowing to parametrise system trajectories using only measured input-output data without explicit model knowledge. For the local predictions, the subsystems rely on communicated assumed trajectories of neighbours. Each subsystem guarantees a small deviation from these trajectories via a consistency constraint. We provide a theoretical analysis of the resulting non-iterative distributed MPC scheme, including proofs of recursive feasibility and (practical) stability. Finally, the approach is successfully applied to a numerical example. |
eng |
dc.language.iso |
eng |
|
dc.publisher |
Frankfurt ; München [u.a.] : Elsevier |
|
dc.relation.ispartofseries |
IFAC-PapersOnLine 55 (2022), Nr. 30 |
|
dc.rights |
CC BY-NC-ND 4.0 Unported |
|
dc.rights.uri |
https://creativecommons.org/licenses/by-nc-nd/4.0 |
|
dc.subject |
Data-based control |
eng |
dc.subject |
distributed control |
eng |
dc.subject |
large-scale systems |
eng |
dc.subject |
linear systems |
eng |
dc.subject |
predictive control |
eng |
dc.subject.ddc |
600 | Technik
|
|
dc.title |
Data-driven distributed MPC of dynamically coupled linear systems |
eng |
dc.type |
Article |
|
dc.type |
Text |
|
dc.relation.essn |
2405-8963 |
|
dc.relation.doi |
https://doi.org/10.1016/j.ifacol.2022.11.080 |
|
dc.bibliographicCitation.issue |
30 |
|
dc.bibliographicCitation.volume |
55 |
|
dc.bibliographicCitation.firstPage |
365 |
|
dc.bibliographicCitation.lastPage |
370 |
|
dc.description.version |
publishedVersion |
eng |
tib.accessRights |
frei zug�nglich |
|