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Data-Driven Modeling of Large-Scale Control Systems at the European Spallation Source (ESS)

Olofsson, Eskil (2026)
Department of Automatic Control
Abstract
Control systems at European Spallation Source (ESS) are large-scale, complex and difficult to model using traditional approaches. Data-driven methods are therefore required to model systems such as the Cryogenic Moderator System (CMS) and Target Helium Cooling System (THCS). This work presents a control-system modeling approach based on the Transformer and Long Short-Term Memory (LSTM), enabling long-range multivariate predictions using control variables as exogenous inputs. The proposed framework integrates these models into a closed-loop setting, enabling iterative, autoregressive, predictions during both training and deployment. The results were promising for the THCS and artificial systems, while performance on the CMS was more... (More)
Control systems at European Spallation Source (ESS) are large-scale, complex and difficult to model using traditional approaches. Data-driven methods are therefore required to model systems such as the Cryogenic Moderator System (CMS) and Target Helium Cooling System (THCS). This work presents a control-system modeling approach based on the Transformer and Long Short-Term Memory (LSTM), enabling long-range multivariate predictions using control variables as exogenous inputs. The proposed framework integrates these models into a closed-loop setting, enabling iterative, autoregressive, predictions during both training and deployment. The results were promising for the THCS and artificial systems, while performance on the CMS was more limited. This discrepancy was likely caused by insufficient system excitation in the available datasets, owing to the absence of beam-on-target operations at ESS to date. While the proposed data-driven framework demonstrates considerable potential, its overall reliability is currently constrained by the limited diversity of operational data and a lack of out-of-domain testing. (Less)
Please use this url to cite or link to this publication:
author
Olofsson, Eskil
supervisor
organization
alternative title
Closed-Loop Modeling of the Cryogenic Moderator System (CMS) and the Target Helium Cooling System (THCS) Using Transformers and LSTMs
year
type
H3 - Professional qualifications (4 Years - )
subject
report number
TFRT-6313
other publication id
0280-5316
language
English
id
9246901
date added to LUP
2026-08-25 10:36:37
date last changed
2026-08-25 10:36:37
@misc{9246901,
  abstract     = {{Control systems at European Spallation Source (ESS) are large-scale, complex and difficult to model using traditional approaches. Data-driven methods are therefore required to model systems such as the Cryogenic Moderator System (CMS) and Target Helium Cooling System (THCS). This work presents a control-system modeling approach based on the Transformer and Long Short-Term Memory (LSTM), enabling long-range multivariate predictions using control variables as exogenous inputs. The proposed framework integrates these models into a closed-loop setting, enabling iterative, autoregressive, predictions during both training and deployment. The results were promising for the THCS and artificial systems, while performance on the CMS was more limited. This discrepancy was likely caused by insufficient system excitation in the available datasets, owing to the absence of beam-on-target operations at ESS to date. While the proposed data-driven framework demonstrates considerable potential, its overall reliability is currently constrained by the limited diversity of operational data and a lack of out-of-domain testing.}},
  author       = {{Olofsson, Eskil}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Data-Driven Modeling of Large-Scale Control Systems at the European Spallation Source (ESS)}},
  year         = {{2026}},
}