Author: Parenti, A.
Paper Title Page
TUPDP033 Applying Model Predictive Control to Regulate Thermal Stability of a Hard X-ray Monochromator Using the Karabo SCADA Framework 579
 
  • M.A. Smith, G. Giovanetti, S. Hauf, I. Karpics, A. Parenti, A. Samadli, L. Samoylova, A. Silenzi, F. Sohn, P. Zalden
    EuXFEL, Schenefeld, Germany
  
  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.  
poster icon Poster TUPDP033 [0.337 MB]  
DOI • reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-TUPDP033  
About • Received ※ 05 October 2023 — Revised ※ 18 October 2023 — Accepted ※ 04 December 2023 — Issued ※ 11 December 2023
Cite • reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)  
 
TH1BCO06 The Karabo Control System 1120
 
  • S. Hauf, N. Anakkappalla, J.T. Bin Taufik, V. Bondar, R. Costa, W. Ehsan, S.G. Esenov, G. Flucke, A. García-Tabarés Valdivieso, G. Giovanetti, D. Goeries, D.G. Hickin, I. Karpics, A. Klimovskaia, A. Parenti, A. Samadli, H. Santos, A. Silenzi, M.A. Smith, F. Sohn, M. Staffehl, C. Youngman
    EuXFEL, Schenefeld, Germany
  
  The Karabo distributed control system has been developed to address the challenging requirements of the European X-ray Free Electron Laser facility*, which include custom-made hardware, and high data rates and volumes. Karabo implements a broker-based SCADA environment**. Extensions to the core framework, called devices, provide control of hardware, monitoring, data acquisition and online processing on distributed hardware. Services for data logging and for configuration management exist. The framework exposes Python and C++ APIs, which enable developers to quickly respond to requirements within an efficient development environment. An AI driven device code generator facilitates prototyping. Karabo’s GUI features an intuitive, coding-free control panel builder. This allows non-software engineers to create synoptic control views. This contribution introduces the Karabo Control System out of the view of application users and software developers. Emphasis is given to Karabo’s asynchronous Python environment. We share experience of running the European XFEL using a clean-sheet developed control system, and discuss the availability of the system as free and open source software.
* Tschentscher, et al. Photon beam transport and scientific instruments at the European XFEL App. Sci.7.6(2017):592
** Hauf, et al. The Karabo distributed control system J.Sync. Rad.26.5(2019):1448ff
 		 
slides icon Slides TH1BCO06 [5.878 MB]  
DOI • reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-TH1BCO06  
About • Received ※ 06 October 2023 — Accepted ※ 03 December 2023 — Issued ※ 12 December 2023  
Cite • reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)