Гібридний фреймворк для адаптивного неперервного контролю на базі нейронних операторів Фур’є
Hybrid adaptive control methods are of high scientific interest and industrial urgency due to their ability to address the weaknesses of both model-driven and data-driven controllers, as the former are reliable and predictable, but rigid and often suboptimal, while the latter provide eventual optima...
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| Datum: | 2026 |
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| Hauptverfasser: | , |
| Format: | Artikel |
| Sprache: | Englisch |
| Veröffentlicht: |
Kamianets-Podilskyi National Ivan Ohiienko University
2026
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| Online Zugang: | https://mcm-tech.kpnu.edu.ua/article/view/354699 |
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| Назва журналу: | Mathematical and computer modelling. Series: Technical sciences |