Skip to main content
Go to the home page of the European Commission (opens in new window)
English en
CORDIS - EU research results
CORDIS

Scalable Control Approximations for Resource Constrained Environments

Project description

Advancing control and decision-making for complex processes

The field of Mixed-Integer Optimal Control (MIOC) is growing, but it still faces unanswered questions due to its complexity and inefficiencies. The ERC-funded SCARCE project aims to enhance optimal control and decision-making for dynamic nonlinear processes occurring on network structures. It delves into complex themes such as decomposition, relaxation, approximation, homogenisation, limiting processes, and weak topologies. Its goal is to discover efficient methods for estimating direct costs, developing nonlinear solvers, and creating decision policies capable of handling uncertainty in critical control tasks with societal impact. SCARCE aims to introduce new theories, develop numerical approximation methods, implement algorithms in software, and conduct proof-of-concept studies. The applications of this research extend to various fields, including energy networks, logistics, disease spreading dynamics, and biomedicine.

Objective

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.

Fields of science (EuroSciVoc)

Programme(s)

Topic(s)

Funding Scheme

HORIZON-ERC - HORIZON ERC Grants

See all projects funded under this funding scheme

Call for proposal

(opens in new window) ERC-2022-COG

See all projects funded under this call

Host institution

TECHNISCHE UNIVERSITAET BRAUNSCHWEIG
Net EU contribution
€ 1 998 500,00
Address
UNIVERSITAETSPLATZ 2
38106 Braunschweig
Germany
Region
Niedersachsen Braunschweig Braunschweig, Kreisfreie Stadt
Activity type
Higher or Secondary Education Establishments
Links
Total cost
€ 1 998 500,00

Beneficiaries (1)