WG 3 - Hybrid and Data-driven modelling

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Overview

The aim is to address control problems built on observed pairs of input-output data. The Action will develop efficient and reliable methods for designing controllers when the underlying model is unidentified or when the underlying laws and processes only allow partial knowledge. While these topics arise in a wide range of potential applications, the Action will focus on control of power systems (solar, wind, smart houses) and construction of digital twins in healthcare and personalised medicine. In connection with industry partners, the Action will explore implementation options that can provide benefits for clean energy and improve healthcare outcomes of European citizens.


Tasks

  1. Approximating the (control to) state law from data
  2. Constructive methods for extremum seeking control
  3. Control of energy systems
  4. Digital twins for personalised medicine

Working group leaders

Leader

Photo of Kathrin Flasskamp

Kathrin Flasskamp, Prof. Dr.

kathrin.flasskamp@uni-saarland.de

Universität des Saarlandes, Campus, 66123 Saarbrücken, Germany

Co-Leader

Photo of Lars Grüne

Lars Grüne, Prof. Dr.

lars.gruene@uni-bayreuth.de

Universität Bayreuth, Universitätsstrasse 30, 95447 Bayreuth, Germany


Working group members (112)


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