KONEST · Kernel-based Methods in Control and Estimation
„Хоризонт Европа“ — Действия „Мария Склодовска-Кюри“
- Период
- 2027-01-01 → 2030-12-31
- Финансиране от ЕС
- 4 592 712 €
- Участници
- 18
- Схема
- HORIZON-TMA-MSCA-DN
Линиите свързват координатора с партньорите. За проекти отпреди 2014 г. CORDIS не винаги дава точни координати. Тези точки са на ниво град или държава.
Накратко на български
Математическите методи с ядра се използват за по-точно управление на сложни системи, като например анализ на нелинейна динамика чрез данни. Това помага за създаването на по-надеждни и ефективни технологии в различни индустрии.
Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.
Цел на проекта
The proposed programme will establish a Doctoral Network in Mathematics with a special focus on Kernel-Based Methods in Control and Estimation. The network aims at advancing the theoretical foundations and practical applications of kernel-based techniques in control and estimation of complex dynamical systems. By bringing together leading researchers and institutions, the project will foster interdisciplinary collaboration and innovation in areas such as state estimation for partial differential equations, data-driven analysis of nonlinear dynamics, and uncertainty quantification in complex systems. The network will also explore the integration of machine learning methods, including physics-informed deep learning and Gaussian process online learning, to enhance control strategies and state estimation in uncertain and nonlinear environments. Additionally, the project will address real-world applications from different technological domains. Furthermore, by incorporating physical prior-knowledge into data-driven control and developing localized sensitivities for efficient learning, the network seeks to create robust, reliable, and efficient methods applicable across various industries. The doctoral network will not only contribute to advancing mathematical knowledge but also strengthen European innovation capacity by training highly skilled researchers equipped to tackle complex mathematical problems. Through collaborative research projects, workshops, and dissemination of findings in top-tier journals and conferences, the network will have a lasting impact on both academia and industry, fostering sustainable development and technological advancement.
Оригинален текст от CORDIS (на английски).
Участници
- TECHNISCHE UNIVERSITAET ILMENAU · IlmenauКоординаторГермания
- BRANDENBURGISCHE TECHNISCHE UNIVERSITAT COTTBUS-SENFTENBERG · CottbusГермания
- CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS · ParisФранция
- EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH · ZuerichШвейцария
- FACULTY OF SCIENCE UNIVERSITY OF ZAGREB · ZagrebХърватия
- INSTITUT NATIONAL DE RECHERCHE EN INFORMATIQUE ET AUTOMATIQUE · Le Chesnay CedexФранция
- RIJKSUNIVERSITEIT GRONINGEN · GroningenНидерландия
- SPEEDGOAT GMBH · LiebefeldНиво държаваШвейцария
- TECHNISCHE UNIVERSITAET CHEMNITZ · ChemnitzГермания
- TECHNISCHE UNIVERSITAT HAMBURG · HamburgГермания
- TECHNISCHE UNIVERSITEIT EINDHOVEN · EindhovenНидерландия
- THE MATHWORKS LIMITED · Cambridge CambsОбединеното кралство
- THE UNIVERSITY OF MANCHESTER · ManchesterОбединеното кралство
- UNIVERSITE DE LILLE · LilleФранция
- UNIVERSITE DE TOULOUSE · ToulouseФранция
- UNIVERSITE PARIS-SACLAY · Gif-Sur-YvetteФранция
- UNIVERSITY OF SOUTHAMPTON · SOUTHAMPTONОбединеното кралство
- University of Novi Sad Faculty of Sciences · Novi SadСърбия
Връзки
Данни: CORDIS, © Европейски съюз