SCARCE
Financiado
Scalable Control Approximations for Resource Constrained Environments
This project aims at making a breakthrough contribution in optimal control and decision making for nonlinear processes that take place on network structures and are dynamic in time and/or space. The setting has a wide range of pot...
This project aims at making a breakthrough contribution in optimal control and decision making for nonlinear processes that take place on network structures and are dynamic in time and/or space. The setting has a wide range of potential domains of applicability, comprising thermal, electric, or fluid dynamics in energy networks, logistics, disease spreading dynamics, or cell signalling in biomedicine. The project will pursue the following objectives: To contribute new theory, to develop numerical approximation methods, to implement algorithmic methods in software, and to conduct proof-of-concept studies. Research in the young field of mixed-integer optimal control (MIOC) has recently seen increased momentum together with numerical approximation algorithms and control theory. Despite initial successes, key questions remain unsolved because of a lack of analytical understanding, a lack of tractable formulations, the unavailability of efficient solvers or the insufficiency of existing implementations. This project focuses on pivotal but poorly understood topics: decomposition, relaxation, and approximation; domains admitting homogenization and limiting processes using weak topologies; tractable approximations of direct costs of decisions; efficient distributed and parallel nonlinear solvers; and robustness of approximate nonlinear decision policies under uncertainty. These key issues appear systematically in a wide range of control tasks of high societal relevance. By addressing them, the project helps to bridge a persistent and pronounced gap in simulation & optimization practice. Due to non-trivial interactions emerging in theory and the unavailability of comprehensive algorithms, these topics cannot be suitably handled by merely combining the respective states of the art. A focused effort to decisively extend MIOC to optimal decisions for dynamics on networks is therefore a timely endeavour that will help to address the challenging demands of practitioners.
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Duración del proyecto: 63 meses
Fecha Inicio: 2023-03-12
Fecha Fin: 2028-06-30
Fecha Fin: 2028-06-30
Línea de financiación: concedida
El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2023-03-12
Línea de financiación objetivo
El proyecto se financió a través de la siguiente ayuda:
ERC-2022-COG:
ERC CONSOLIDATOR GRANTS
Cerrada
hace 2 años
Presupuesto
El presupuesto total del proyecto asciende a
2M€
Líder del proyecto
TECHNISCHE UNIVERSITAET BRAUNSCHWEIG
No se ha especificado una descripción o un objeto social para esta compañía.
Perfil tecnológico
TRL
4-5
Perfil tecnológico
TRL
4-5