Author: Martinelli, V.
Paper Title Page
TUBL05 Pysmlib: A Python Finite State Machine Library for EPICS 330
  • D. Marcato, G. Arena, D. Bortolato, F. Gelain, G. Lilli, V. Martinelli, E. Munaron, M. Roetta, G. Savarese
    INFN/LNL, Legnaro (PD), Italy
  • M.A. Bellato
    INFN- Sez. di Padova, Padova, Italy
  In the field of Experimental Physics and Industrial Control Systems (EPICS)*, the traditional tool to implement high level procedures is the Sequencer*. While this is a mature, fast, and well-proven software, it comes with some drawbacks. For example, it’s based on a custom C-like programming language which may be unfamiliar to new users and it often results in complex, hard to read code. This paper presents pysmlib, a free and open source Python library developed as a simpler alternative to the EPICS Sequencer. The library exposes a simple interface to develop event-driven Finite State Machines (FSM), where the inputs are connected to Channel Access Process Variables (PV) thanks to the PyEpics** integration. Other features include parallel FSM with multi-threading support and input sharing, timers, and an integrated watchdog logic. The library offers a lower barrier to enter and greater extensibility thanks to the large ecosystem of scientific and engineering python libraries, making it a perfect fit for modern control system requirements. Pysmlib has been deployed in multiple projects at INFN Legnaro National Laboratories (LNL), proving its robustness and flexibility.
* L. R. Dalesio, M. R. Kraimer, and A. J. Kozubal. "EPICS architecture." ICALEPCS. Vol. 91. 1991.
** M. Newville, et al., pyepics/pyepics Zenodo.
slides icon Slides TUBL05 [1.705 MB]  
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About • Received ※ 08 October 2021       Revised ※ 22 October 2021       Accepted ※ 22 December 2021       Issue date ※ 10 February 2022
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TUPV016 Design and Development of the New Diagnostics Control System for the SPES Project at INFN-LNL 428
  • G. Savarese, G. Arena, D. Bortolato, F. Gelain, D. Marcato, V. Martinelli, E. Munaron, M. Roetta
    INFN/LNL, Legnaro (PD), Italy
  The need to get finer data to describe the beam is a relevant topic for all laboratories. For the SPES project at Laboratori Nazionali di Legnaro (LNL) a new diagnostic control system with more performing hardware, with respect to the one used in legacy accelerators based on Versabus Module Eurocard (VME) ADCs, has been developed. The new system uses a custom hardware to acquire signals in real time. These data and ancillary operations are managed by a control system based on the Experimental Physics and Industrial Control System (EPICS) standard and shown to users on a Control System Studio (CSS) graphical user interface. The new system improves the basic functionalities, current read-back over Beam Profilers (BP) and Faraday Cups (FC) and handlings control, with new features such as: multiple hardware gain levels selection, broken wires correction through polynomial interpolation and roto-translations taking into account alignment parameters. Another important feature, integrated with the usage of a python Finite State Machine (FSM), is the capability to control an emittance meter to quickly acquire data and calculate beam longitudinal phase space through the scubeex method.  
poster icon Poster TUPV016 [2.235 MB]  
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About • Received ※ 28 September 2021       Revised ※ 02 November 2021       Accepted ※ 20 November 2021       Issue date ※ 08 March 2022
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THAL03 Machine Learning Based Middle-Layer for Autonomous Accelerator Operation and Control 797
  • S. Pioli, B. Buonomo, D. Di Giovenale, C. Di Giulio, L.G. Foggetta, G. Piermarini
    LNF-INFN, Frascati, Italy
  • F. Cardelli, P. Ciuffetti
    INFN/LNF, Frascati, Italy
  • V. Martinelli
    INFN/LNL, Legnaro (PD), Italy
  The Singularity project, led by National Laboratories of Frascati of the National Institute for Nuclear Physics (INFN-LNF), aim to develop automated machine-independent middle-layer to control accelerator operation through machine learning (ML) algorithms like Reinforcement Learning (RL) and Cluster integrated with accelerator’s sub-systems. In this work we will present architecture and of the middle-layer made with main purpose to drive user requests through the control framework backend and allow users to enjoy a better User Experience (UX) handling system performances without facing problems due to the interaction with control system. We will report the strategy to develop autonomous operation control with RL algorithms together with the fault detection capability improved by Clustering approach as breakdown and waveguide and RF cavity thermal stability monitor. Results of the first period of operation of this system, currently operating at the electron-positron LINAC of the Dafne complex in Frascati, autonomously controlling accelerator performance in terms of beam transport, beam current optimization and RF cavity phase-jitter compensation will be reported.  
slides icon Slides THAL03 [0.960 MB]  
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About • Received ※ 19 October 2021       Accepted ※ 22 December 2021       Issue date ※ 16 February 2022  
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