Machine Learning for Modelling and Control

  • Adres

    Groene Loper 19, Flux

    5612 AP Eindhoven

    Nederland

  • Postadres

    Department of Electrical Engineering, P.O. Box 513

    5600 MB Eindhoven

    Nederland

Organisatieprofiel

Introductie / missie

Focus on data-driven modelling (identification) and control of complex physical/chemical systems, in particular in the high-tech and process technology domains.

Over de organisatie

The research activities aim at efficiently addressing modelling and control of nonlinear/time-varying behavior of systems in these domains by developing a fusion of system identification, control and machine learning methods. The resulting methods automatically construct dynamical models capturing user specified aspects of the system behavior. In terms of control, policies/algorithms are automatically synthesized that realize a desired behavior of a system by manipulating its actuators. A strong emphasis is put on data-driven structural exploration of the underlying system dynamics, like identification of structured nonlinear systems, and data-driven synthesis of control polices. In this exploration, learning the associated model accuracy/control performance versus complexity trade-off plays an important role. Another focus of the research activities is the development of automated methods that use of surrogate models with linear, but varying dynamical representation concepts, such as linear parameter-varying models, to facilitate technological evolution of currently wide-spread methodologies based on the linear time-invariant framework in engineering.

VN Doelstellingen voor duurzame ontwikkeling

In 2015 stemden de VN-lidstaten in met 17 wereldwijde duurzame ontwikkelingsdoelstellingen (Sustainable Development Goals, SDG's) om armoede te beëindigen, de planeet te beschermen en voor iedereen welvaart te garanderen. Ons werk draagt bij aan de volgende duurzame ontwikkelingsdoelstelling(en):

  • SDG 9 – Industrie, innovatie en infrastructuur

Vingerafdruk

Verdiep u in de onderzoeksgebieden waarop Machine Learning for Modelling and Control actief is. Deze onderwerplabels komen uit het werk van de leden van deze organisatie. Samen vormen ze een unieke vingerafdruk.

Netwerk

Recente externe samenwerking op landen-/regioniveau. Duik in de details door op de stippen te klikken of