Details
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 146-152 |
| Seitenumfang | 7 |
| Fachzeitschrift | IFAC-PapersOnLine |
| Jahrgang | 58 |
| Ausgabenummer | 18 |
| Frühes Online-Datum | 25 Sept. 2024 |
| Publikationsstatus | Veröffentlicht - 2024 |
| Veranstaltung | 8th IFAC Conference on Nonlinear Model Predictive Control, NMPC 2024 - Kyoto, Japan Dauer: 21 Aug. 2024 → 24 Aug. 2024 |
Abstract
This paper presents a robust MPC scheme for linear systems subject to time-varying, uncertain constraints that arise from uncertain environments. The predicted input sequence is parameterized over future environment states to guarantee constraint satisfaction despite an imprecise environment prediction and unknown evolution of the future constraints. We provide theoretical guarantees for recursive feasibility and asymptotic convergence. Finally, a brief simulation example showcases our results.
ASJC Scopus Sachgebiete
- Ingenieurwesen (insg.)
- Steuerungs- und Systemtechnik
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in: IFAC-PapersOnLine, Jahrgang 58, Nr. 18, 2024, S. 146-152.
Publikation: Beitrag in Fachzeitschrift › Konferenzaufsatz in Fachzeitschrift › Forschung › Peer-Review
}
TY - JOUR
T1 - Disturbance feedback-based model predictive control in uncertain dynamic environments
AU - Buschermöhle, Philipp
AU - Jouini, Taouba
AU - Lilge, Torsten
AU - Müller, Matthias A.
N1 - Publisher Copyright: Copyright © 2024 The Authors.
PY - 2024
Y1 - 2024
N2 - This paper presents a robust MPC scheme for linear systems subject to time-varying, uncertain constraints that arise from uncertain environments. The predicted input sequence is parameterized over future environment states to guarantee constraint satisfaction despite an imprecise environment prediction and unknown evolution of the future constraints. We provide theoretical guarantees for recursive feasibility and asymptotic convergence. Finally, a brief simulation example showcases our results.
AB - This paper presents a robust MPC scheme for linear systems subject to time-varying, uncertain constraints that arise from uncertain environments. The predicted input sequence is parameterized over future environment states to guarantee constraint satisfaction despite an imprecise environment prediction and unknown evolution of the future constraints. We provide theoretical guarantees for recursive feasibility and asymptotic convergence. Finally, a brief simulation example showcases our results.
KW - Disturbance Feedback
KW - Model Predictive Control
KW - Time-Varying Constraints
UR - http://www.scopus.com/inward/record.url?scp=85206092433&partnerID=8YFLogxK
U2 - 10.48550/arXiv.2404.09893
DO - 10.48550/arXiv.2404.09893
M3 - Conference article
AN - SCOPUS:85206092433
VL - 58
SP - 146
EP - 152
JO - IFAC-PapersOnLine
JF - IFAC-PapersOnLine
SN - 2405-8971
IS - 18
T2 - 8th IFAC Conference on Nonlinear Model Predictive Control, NMPC 2024
Y2 - 21 August 2024 through 24 August 2024
ER -