Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | 2022 European Control Conference (ECC) |
| Erscheinungsort | [Piscataway, NJ] |
| Seiten | 1778-1783 |
| Seitenumfang | 6 |
| ISBN (elektronisch) | 978-3-9071-4407-7 |
| Publikationsstatus | Veröffentlicht - 2022 |
| Veranstaltung | 2022 European Control Conference (ECC) - London, Großbritannien / Vereinigtes Königreich Dauer: 12 Juli 2022 → 15 Juli 2022 |
Abstract
This paper introduces a data-based moving horizon estimation (MHE) scheme for linear time-invariant discrete-time systems. The scheme solely relies on collected data with-out employing any system identification step. Robust global exponential stability of the data-based MHE is proven under standard assumptions for the case where the online output measurements are corrupted by some non-vanishing measurement noise. A simulation example illustrates the behavior of the data-based MHE scheme.
ASJC Scopus Sachgebiete
- Entscheidungswissenschaften (insg.)
- Informationssysteme und -management
- Informatik (insg.)
- Artificial intelligence
- Mathematik (insg.)
- Steuerung und Optimierung
- Ingenieurwesen (insg.)
- Steuerungs- und Systemtechnik
- Informatik (insg.)
- Computernetzwerke und -kommunikation
- Mathematik (insg.)
- Modellierung und Simulation
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2022 European Control Conference (ECC). [Piscataway, NJ], 2022. S. 1778-1783.
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Data-Based Moving Horizon Estimation for Linear Discrete-Time Systems
AU - Wolff, Tobias M.
AU - Lopez, Victor G.
AU - Müller, Matthias A.
N1 - Funding Information: *This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 948679). 1Leibniz University Hannover, Institute of Control, 30167 Hannover, Germany. E-mail:
PY - 2022
Y1 - 2022
N2 - This paper introduces a data-based moving horizon estimation (MHE) scheme for linear time-invariant discrete-time systems. The scheme solely relies on collected data with-out employing any system identification step. Robust global exponential stability of the data-based MHE is proven under standard assumptions for the case where the online output measurements are corrupted by some non-vanishing measurement noise. A simulation example illustrates the behavior of the data-based MHE scheme.
AB - This paper introduces a data-based moving horizon estimation (MHE) scheme for linear time-invariant discrete-time systems. The scheme solely relies on collected data with-out employing any system identification step. Robust global exponential stability of the data-based MHE is proven under standard assumptions for the case where the online output measurements are corrupted by some non-vanishing measurement noise. A simulation example illustrates the behavior of the data-based MHE scheme.
UR - http://www.scopus.com/inward/record.url?scp=85136691216&partnerID=8YFLogxK
U2 - 10.23919/ECC55457.2022.9838331
DO - 10.23919/ECC55457.2022.9838331
M3 - Conference contribution
SN - 978-1-6654-9733-6
SP - 1778
EP - 1783
BT - 2022 European Control Conference (ECC)
CY - [Piscataway, NJ]
T2 - 2022 European Control Conference (ECC)
Y2 - 12 July 2022 through 15 July 2022
ER -