Abstract
A computationally efficient Model-Predictive Control (MPC) approach is proposed for systems with unknown delay using only input/output data. We use the Koopman operator framework and the related Hankel Alternative View of Koopman (HAVOK) algorithm to identify a model in a basis of projected time-delay coordinates and demonstrate a novel MPC structure that reduces and bounds the computational complexity. The proposed HAVOK-MPC approach is validated experimentally on a laboratory-scale District Heating System (DHS), demonstrating excellent prediction and tracking performance while only requiring knowledge of a conservative upper bound on the system delay.
Originalsprog | Engelsk |
---|---|
Bogserie | IFAC-PapersOnLine |
Vol/bind | 56 |
Udgave nummer | 2 |
Sider (fra-til) | 2238-2243 |
Antal sider | 6 |
ISSN | 1474-6670 |
DOI | |
Status | Udgivet - nov. 2023 |
Begivenhed | 22nd IFAC World Congress 2023 - Yokohama, Japan Varighed: 9 jul. 2023 → 14 jul. 2023 https://www.ifac2023.org/ |
Konference
Konference | 22nd IFAC World Congress 2023 |
---|---|
Land/Område | Japan |
By | Yokohama |
Periode | 09/07/2023 → 14/07/2023 |
Internetadresse |