ICALEPCS2019 - List of Authors (Lonza, M.)

Paper	Title	Page
MOSH4001	A Library of Fundamental Building Blocks for Experimental Control Software	653
MOPHA130	use link to see paper's listing under its alternate paper code
	M. Scarcia, R. Borghes, M. Lonza, M. Manfredda, R. Mincigrucci, E. Pedersoli Elettra-Sincrotrone Trieste S.C.p.A., Basovizza, Italy
	In many experimental facilities there is a rising interest by users and beamline scientists to take part in the experiment control software development process. This necessity arises from the flexibility and adaptability of many beamlines, that can run very different experiments, requiring changes in the software even during beamtimes. On the other side, we still need a professional and controlled approach in order to be able to maintain the software efficiently. Our proposed solution is to exploit the object oriented nature of programming languages to create a library that provides a uniform interface both to the different controlled devices (e.g. motors) and to experimental procedures (e.g. scans). Every component and procedure can be represented as an object, a building block for experiment control scripts. We can thus provide the scientists with a powerful tool for implementing highly flexible control software to run experiments. Furthermore, a library makes the development of experiment control scripts easier and quicker for software developers. In any case we are able to protect the most sensitive structures (e.g. control systems) beneath a strong and trusted software layer.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2019-MOSH4001
About •	paper received ※ 30 September 2019 paper accepted ※ 09 October 2019 issue date ※ 30 August 2020
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

WEPHA021	Free-Electron Laser Optimization with Reinforcement Learning	1122
	N. Bruchon, G. Fenu, F.A. Pellegrino, E. Salvato University of Trieste, Trieste, Italy G. Gaio, M. Lonza Elettra-Sincrotrone Trieste S.C.p.A., Basovizza, Italy
	Reinforcement Learning (RL) is one of the most promising techniques in Machine Learning because of its modest computational requirements with respect to other algorithms. RL uses an agent that takes actions within its environment to maximize a reward related to the goal it is designed to achieve. We have recently used RL as a model-free approach to improve the performance of the FERMI Free Electron Laser. A number of machine parameters are adjusted to find the optimum FEL output in terms of intensity and spectral quality. In particular we focus on the problem of the alignment of the seed laser with the electron beam, initially using a simplified model and then applying the developed algorithm on the real machine. This paper reports the results obtained and discusses pros and cons of this approach with plans for future applications.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2019-WEPHA021
About •	paper received ※ 30 September 2019 paper accepted ※ 09 October 2019 issue date ※ 30 August 2020
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

WEPHA097	Development of a Tango Interface for the Siemens-Based Control System of the Elettra Infrastructure Plants	1321
	P. Michelini, I. Ferigutti, F. Giacuzzo, M. Lonza, G. Scalamera, G. Strangolino, M. Trevi Elettra-Sincrotrone Trieste S.C.p.A., Basovizza, Italy
	The control system of the Elettra Sincrotrone Trieste infrastructure plants (cooling water, air conditioning, electricity, etc.) consists of several Siemens PLCs connected by an Ethernet network and a number of management stations running the Siemens Desigo software for high-level operation and monitoring, graphical display of the process variables, automatic alarm distribution and a wide range of different data analysis features. No external interface has been realized so far to connect Desigo to the Elettra and FERMI accelerator control systems based on Tango, making it difficult for the control room operators to monitor the conventional plant operation and parameters (temperature, humidity, water pressure, etc.), which are essential for the accelerator performance and reliability. This paper describes the development of a dedicated Desigo application to make selected process variables externally visible to a specific Tango device server, which then enables the use of all the tools provided by this software framework to implement graphical interfaces, alarms, archiving, etc. New proposals and developments to expand and improve the system are also discussed.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2019-WEPHA097
About •	paper received ※ 30 September 2019 paper accepted ※ 09 October 2019 issue date ※ 30 August 2020
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

Paper

Title

Page

MOSH4001

A Library of Fundamental Building Blocks for Experimental Control Software

653

MOPHA130

use link to see paper's listing under its alternate paper code

M. Scarcia, R. Borghes, M. Lonza, M. Manfredda, R. Mincigrucci, E. Pedersoli
Elettra-Sincrotrone Trieste S.C.p.A., Basovizza, Italy

In many experimental facilities there is a rising interest by users and beamline scientists to take part in the experiment control software development process. This necessity arises from the flexibility and adaptability of many beamlines, that can run very different experiments, requiring changes in the software even during beamtimes. On the other side, we still need a professional and controlled approach in order to be able to maintain the software efficiently. Our proposed solution is to exploit the object oriented nature of programming languages to create a library that provides a uniform interface both to the different controlled devices (e.g. motors) and to experimental procedures (e.g. scans). Every component and procedure can be represented as an object, a building block for experiment control scripts. We can thus provide the scientists with a powerful tool for implementing highly flexible control software to run experiments. Furthermore, a library makes the development of experiment control scripts easier and quicker for software developers. In any case we are able to protect the most sensitive structures (e.g. control systems) beneath a strong and trusted software layer.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2019-MOSH4001

About •

paper received ※ 30 September 2019 paper accepted ※ 09 October 2019 issue date ※ 30 August 2020

Export •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

WEPHA021

Free-Electron Laser Optimization with Reinforcement Learning

1122

N. Bruchon, G. Fenu, F.A. Pellegrino, E. Salvato
University of Trieste, Trieste, Italy
G. Gaio, M. Lonza
Elettra-Sincrotrone Trieste S.C.p.A., Basovizza, Italy

Reinforcement Learning (RL) is one of the most promising techniques in Machine Learning because of its modest computational requirements with respect to other algorithms. RL uses an agent that takes actions within its environment to maximize a reward related to the goal it is designed to achieve. We have recently used RL as a model-free approach to improve the performance of the FERMI Free Electron Laser. A number of machine parameters are adjusted to find the optimum FEL output in terms of intensity and spectral quality. In particular we focus on the problem of the alignment of the seed laser with the electron beam, initially using a simplified model and then applying the developed algorithm on the real machine. This paper reports the results obtained and discusses pros and cons of this approach with plans for future applications.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2019-WEPHA021

About •

paper received ※ 30 September 2019 paper accepted ※ 09 October 2019 issue date ※ 30 August 2020

Export •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

WEPHA097

Development of a Tango Interface for the Siemens-Based Control System of the Elettra Infrastructure Plants

1321

P. Michelini, I. Ferigutti, F. Giacuzzo, M. Lonza, G. Scalamera, G. Strangolino, M. Trevi
Elettra-Sincrotrone Trieste S.C.p.A., Basovizza, Italy

The control system of the Elettra Sincrotrone Trieste infrastructure plants (cooling water, air conditioning, electricity, etc.) consists of several Siemens PLCs connected by an Ethernet network and a number of management stations running the Siemens Desigo software for high-level operation and monitoring, graphical display of the process variables, automatic alarm distribution and a wide range of different data analysis features. No external interface has been realized so far to connect Desigo to the Elettra and FERMI accelerator control systems based on Tango, making it difficult for the control room operators to monitor the conventional plant operation and parameters (temperature, humidity, water pressure, etc.), which are essential for the accelerator performance and reliability. This paper describes the development of a dedicated Desigo application to make selected process variables externally visible to a specific Tango device server, which then enables the use of all the tools provided by this software framework to implement graphical interfaces, alarms, archiving, etc. New proposals and developments to expand and improve the system are also discussed.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2019-WEPHA097

About •

paper received ※ 30 September 2019 paper accepted ※ 09 October 2019 issue date ※ 30 August 2020

Export •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)