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| TUPDP033 |
Applying Model Predictive Control to Regulate Thermal Stability of a Hard X-ray Monochromator Using the Karabo SCADA Framework |
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- M.A. Smith, G. Giovanetti, S. Hauf, I. Karpics, A. Parenti, A. Samadli, L. Samoylova, A. Silenzi, F. Sohn, P. Zalden
EuXFEL, Schenefeld, Germany
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Model Predictive Control (MPC) is an advanced method of process control whereby a model is developed for a real-life system and an optimal control solution is then calculated and applied to control the system. At each time step, the MPC controller uses the system model and system state to minimize a cost function for optimal control. The Karabo SCADA Framework is a distributed control system developed specifically for European XFEL facility, consisting of tens of thousands of hardware and software devices and over two million attributes to track system state. This contribution describes the application of the Python MPC Toolbox within the Karabo SCADA Framework to solve a monochromator temperature control problem. Additionally, the experiences gained in this solution have led to a generic method to apply MPC to any group of Karabo SCADA devices.
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Poster TUPDP033 [0.337 MB]
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| DOI • |
reference for this paper
※ doi:10.18429/JACoW-ICALEPCS2023-TUPDP033
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| About • |
Received ※ 05 October 2023 — Revised ※ 18 October 2023 — Accepted ※ 04 December 2023 — Issued ※ 11 December 2023 |
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