The IRIS project, a recently approved Italian research infrastructure, aims to advance HTS (High-Temperature Superconductors) technology for use in particle accelerators and society applications. Within this project, ongoing research focuses on developing an HTS dipole magnet, with a strong commitment on selecting the most suitable winding technology. Leading contenders include No-Insulation and Controlled-Insulation coils, known for their stability and self-protection features. However, challenges like prolonged charging times persist. This paper explores advanced techniques in Nonlinear Optimal Control theory to address this issue, through an algorithm for optimizing input current profiles using a lumped-parameters model of an HTS device. This theory enables the optimization of virtually any system by defining tailored cost functions that incorporate state variables, inputs, and outputs over time. This paper introduces these concepts to the magnet science community, offering enhanced control and automation capabilities for superconducting magnets, contributing to sustainable technology development for current and future facilities

Nonlinear Optimal Control of No-Insulation and Controlled-Insulation HTS Coils and Magnets / L. Balconi, E. De Matteis, L. Rossi, C. Santini, S. Sorti, M. Statera. - In: IEEE TRANSACTIONS ON APPLIED SUPERCONDUCTIVITY. - ISSN 1051-8223. - (2024), pp. 1-5. [Epub ahead of print] [10.1109/TASC.2024.3369009]

Nonlinear Optimal Control of No-Insulation and Controlled-Insulation HTS Coils and Magnets

L. Balconi
Primo
;
L. Rossi;S. Sorti
Penultimo
;
2024

Abstract

The IRIS project, a recently approved Italian research infrastructure, aims to advance HTS (High-Temperature Superconductors) technology for use in particle accelerators and society applications. Within this project, ongoing research focuses on developing an HTS dipole magnet, with a strong commitment on selecting the most suitable winding technology. Leading contenders include No-Insulation and Controlled-Insulation coils, known for their stability and self-protection features. However, challenges like prolonged charging times persist. This paper explores advanced techniques in Nonlinear Optimal Control theory to address this issue, through an algorithm for optimizing input current profiles using a lumped-parameters model of an HTS device. This theory enables the optimization of virtually any system by defining tailored cost functions that incorporate state variables, inputs, and outputs over time. This paper introduces these concepts to the magnet science community, offering enhanced control and automation capabilities for superconducting magnets, contributing to sustainable technology development for current and future facilities
Superconducting magnets; HTS; Non-Insualted; Control; Computational modeling; Electromagnetics;
Settore FIS/01 - Fisica Sperimentale
2024
23-feb-2024
Article (author)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/1032608
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