Optimizing Ultra-High Vacuum Control in Electron Storage Rings Using Fuzzy Control and Estimation of Pumping Speed by Neural Networks with Molflow+

Author:

Seangsri Soontaree1,Wanglomklang Thanasak2,Khaewnak Nopparut3,Yachum Nattawat4,Srisertpol Jiraphon2ORCID

Affiliation:

1. Mechatronics Engineering Program, Institute of Engineering, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand

2. School of Mechanical Engineering, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand

3. School of Mechatronics Engineering, Rajamangala University of Technology Tawan-ok, Chonburi 20110, Thailand

4. Synchrotron Light Research Institute, Nakhon Ratchasima 30000, Thailand

Abstract

This paper presents the design of a fuzzy-controller-based ultra-high vacuum pressure control system and its performance evaluation for a sputter-ion vacuum pump used in the electron storage ring at the Synchrotron Light Research Institute (Public Organization) in Thailand. The production of synchrotron light requires advanced vacuum technology to maintain stability and prevent interference of electrons in an ultra-high vacuum pressure environment of about 10−9 Torr. The presence of heat and gas rupture from the pipe wall can affect the quality of the light in that area. The institute currently uses a sputter-ion vacuum pump which is costly and requires significant effort to quickly reduce pressure increases in the area. Maintaining stable vacuum pressure throughout electron motion is essential in order to ensure the quality of the light. This research demonstrates a procedure for evaluating the performance of a sputter-ion vacuum pump using a mathematical model generated by a neural network and Molflow+ software. The model is used to estimate the pumping speed of the vacuum pump and to design a fuzzy control system for the ultra-high vacuum system. The study also includes a leakage rate check for the vacuum system.

Funder

Synchrotron Light Research Institute

Publisher

MDPI AG

Subject

Information Systems and Management,Computer Networks and Communications,Modeling and Simulation,Control and Systems Engineering,Software

Reference42 articles.

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5. Bertolini, L. (2023, January 01). Ion Pumps. Presented at The U.S. Particle Accelerator School, Lawrence Livermore National Laboratory, 10–14 June 2002, Available online: https://uspas.fnal.gov/materials/02Yale/05_IonPumps.pdf.

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