In this article, we propose an online method to estimate an approximate linear model of a vertically unstable tokamak plasma to consequently adapt the parameters of a Vertical Stabilization controller. The identification procedure is based on the Dynamic Mode Decomposition with control approach, while the tuning procedure takes advantage of linear control theory to impose the desired crossing frequency and gain margins. The proposed technique is aimed at controlling ITER elongated plasmas using the VS3 stabilization coils, located inside the vessel. The effectiveness of the method is proven by means of numerical simulations carried out with the CREATE-NL+ free boundary evolutionary code, also considering the presence of realistic measurement noise levels.

A data-driven Vertical Stabilization system for the ITER tokamak based on Dynamic Mode Decomposition / di Grazia, L. E.; Mattei, M.; Mele, A.; Pironti, A.. - In: JOURNAL OF THE FRANKLIN INSTITUTE. - ISSN 0016-0032. - 361:2(2024), pp. 816-833. [10.1016/j.jfranklin.2023.12.027]

A data-driven Vertical Stabilization system for the ITER tokamak based on Dynamic Mode Decomposition

Mattei M.;Mele A.;Pironti A.
2024

Abstract

In this article, we propose an online method to estimate an approximate linear model of a vertically unstable tokamak plasma to consequently adapt the parameters of a Vertical Stabilization controller. The identification procedure is based on the Dynamic Mode Decomposition with control approach, while the tuning procedure takes advantage of linear control theory to impose the desired crossing frequency and gain margins. The proposed technique is aimed at controlling ITER elongated plasmas using the VS3 stabilization coils, located inside the vessel. The effectiveness of the method is proven by means of numerical simulations carried out with the CREATE-NL+ free boundary evolutionary code, also considering the presence of realistic measurement noise levels.
2024
A data-driven Vertical Stabilization system for the ITER tokamak based on Dynamic Mode Decomposition / di Grazia, L. E.; Mattei, M.; Mele, A.; Pironti, A.. - In: JOURNAL OF THE FRANKLIN INSTITUTE. - ISSN 0016-0032. - 361:2(2024), pp. 816-833. [10.1016/j.jfranklin.2023.12.027]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/988559
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