A cross platform validation methodology for nuclear grade model predictive control using open-source tools; Journal of Nuclear Science and Technology; Vol. 63, iss. 10
| Parent link: | Journal of Nuclear Science and Technology.— .— Abingdon: Taylor & Francis Ltd. Vol. 63, iss. 10.— 2026.— P. 1163-1208 |
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| Sumari: | This paper presents a cross-platform validation methodology for Model Predictive Control (MPC) systems in nuclear applications, using open-source tools. The approach employs a dual framework validation strategy: a commercially validated MATLAB/Simulink implementation serves as the reference benchmark, while an equivalent Python-based implementation is systematically verified. The methodology is demonstrated through a steam generator control case study for a Low Temperature Reactor (LTR), using a simplified lumped parameter model linearized at five operating points. Controller performance was quantitatively compared across 13 transient scenarios using Normalized Root Mean Square Deviation (NRMSD), with all key outputs showing NRMSD < 0.5%. The MPC strategy reduced water level overshoot by 48% and settling time by 62% compared to conventional PID control, while effectively handling constraints and non-minimum phase dynamics. Results confirm that open-source platforms can serve as credible environments for prototyping nuclear grade control algorithms, providing a transparent pathway from design to deployment Текстовый файл AM_Agreement |
| Idioma: | anglès |
| Publicat: |
2026
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| Matèries: | |
| Accés en línia: | https://doi.org/10.1080/00223131.2026.2679276 |
| Format: | Electrònic Capítol de llibre |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=688427 |
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| 200 | 1 | |a A cross platform validation methodology for nuclear grade model predictive control using open-source tools |f H. Abdelghani, A. Goryunov | |
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| 330 | |a This paper presents a cross-platform validation methodology for Model Predictive Control (MPC) systems in nuclear applications, using open-source tools. The approach employs a dual framework validation strategy: a commercially validated MATLAB/Simulink implementation serves as the reference benchmark, while an equivalent Python-based implementation is systematically verified. The methodology is demonstrated through a steam generator control case study for a Low Temperature Reactor (LTR), using a simplified lumped parameter model linearized at five operating points. Controller performance was quantitatively compared across 13 transient scenarios using Normalized Root Mean Square Deviation (NRMSD), with all key outputs showing NRMSD < 0.5%. The MPC strategy reduced water level overshoot by 48% and settling time by 62% compared to conventional PID control, while effectively handling constraints and non-minimum phase dynamics. Results confirm that open-source platforms can serve as credible environments for prototyping nuclear grade control algorithms, providing a transparent pathway from design to deployment | ||
| 336 | |a Текстовый файл | ||
| 371 | 0 | |a AM_Agreement | |
| 461 | 1 | |t Journal of Nuclear Science and Technology |c Abingdon |n Taylor & Francis Ltd. | |
| 463 | 1 | |t Vol. 63, iss. 10 |v P. 1163-1208 |d 2026 | |
| 610 | 1 | |a model predictive control (MPC) | |
| 610 | 1 | |a nuclear steam generator | |
| 610 | 1 | |a neutron kinetics | |
| 610 | 1 | |a dynamic simulation | |
| 610 | 1 | |a MATLAB | |
| 610 | 1 | |a python | |
| 610 | 1 | |a open-source software | |
| 610 | 1 | |a электронный ресурс | |
| 610 | 1 | |a труды учёных ТПУ | |
| 700 | 1 | |a Abdelgani (Abdelgani) |g Husseini Makhmud Mokhamed Makhmud |9 H. M. | |
| 701 | 1 | |a Goryunov |b A. G. |c Specialist in the field of automatic control |c head of the Department Tomsk Polytechnic University, doctor of technical Sciences |f 1979- |g Aleksey Germanovich |9 16825 | |
| 712 | 0 | 2 | |a Национальный исследовательский Томский политехнический университет |b Инженерная школа ядерных технологий |c (2017- ) |9 28303 |
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| 856 | 4 | 0 | |u https://doi.org/10.1080/00223131.2026.2679276 |z https://doi.org/10.1080/00223131.2026.2679276 |
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