HAVOK Model Predictive Control for Time-Delay Systems with Applications to District Heating

Christian M. Jensen; Mathias C. Frederiksen; Carsten S. Kallesøe; Jeppe N. Jensen; Laurits H. Andersen; Roozbeh Izadi-Zamanabadi

doi:10.1016/j.ifacol.2023.10.1187

HAVOK Model Predictive Control for Time-Delay Systems with Applications to District Heating

Christian M. Jensen, Mathias C. Frederiksen, Carsten S. Kallesøe, Jeppe N. Jensen, Laurits H. Andersen, Roozbeh Izadi-Zamanabadi

Research output: Contribution to journal › Conference article in Journal › Research › peer-review

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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.

Original language	English
Book series	IFAC-PapersOnLine
Volume	56
Issue number	2
Pages (from-to)	2238-2243
Number of pages	6
ISSN	1474-6670
DOIs	https://doi.org/10.1016/j.ifacol.2023.10.1187
Publication status	Published - Nov 2023
Event	22nd IFAC World Congress 2023 - Yokohama, Japan Duration: 9 Jul 2023 → 14 Jul 2023 https://www.ifac2023.org/

Conference

Conference	22nd IFAC World Congress 2023
Country/Territory	Japan
City	Yokohama
Period	09/07/2023 → 14/07/2023
Internet address	https://www.ifac2023.org/

Keywords

Delay systems
District heating systems
Dynamic Mode Decomposition
Koopman operator
Model Predictive Control
Modelling and system identification

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Cite this

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title = "HAVOK Model Predictive Control for Time-Delay Systems with Applications to District Heating",

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.",

keywords = "Delay systems, District heating systems, Dynamic Mode Decomposition, Koopman operator, Model Predictive Control, Modelling and system identification",

author = "Jensen, {Christian M.} and Frederiksen, {Mathias C.} and Kalles{\o}e, {Carsten S.} and Jensen, {Jeppe N.} and Andersen, {Laurits H.} and Roozbeh Izadi-Zamanabadi",

year = "2023",

month = nov,

doi = "10.1016/j.ifacol.2023.10.1187",

language = "English",

volume = "56",

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journal = "IFAC-PapersOnLine",

issn = "1474-6670",

publisher = "Elsevier",

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note = "22nd IFAC World Congress 2023 ; Conference date: 09-07-2023 Through 14-07-2023",

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AU - Jensen, Christian M.

AU - Frederiksen, Mathias C.

AU - Kallesøe, Carsten S.

AU - Jensen, Jeppe N.

AU - Andersen, Laurits H.

AU - Izadi-Zamanabadi, Roozbeh

PY - 2023/11

Y1 - 2023/11

N2 - 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.

AB - 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.

KW - Delay systems

KW - District heating systems

KW - Dynamic Mode Decomposition

KW - Koopman operator

KW - Model Predictive Control

KW - Modelling and system identification

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U2 - 10.1016/j.ifacol.2023.10.1187

DO - 10.1016/j.ifacol.2023.10.1187

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SN - 1474-6670

VL - 56

SP - 2238

EP - 2243

JO - IFAC-PapersOnLine

JF - IFAC-PapersOnLine

IS - 2

T2 - 22nd IFAC World Congress 2023

Y2 - 9 July 2023 through 14 July 2023

ER -

HAVOK Model Predictive Control for Time-Delay Systems with Applications to District Heating

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