Machine Learning for Modelling and Control

  • Groene Loper 19, Flux

    5612 AP Eindhoven


  • P.O. Box 513, Department of Electrical Engineering

    5600 MB Eindhoven


Organization profile

Introduction / mission

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

Organisational profile

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.

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    Research Output

    Automating data-driven modelling of dynamical systems: an evolutionary computation approach

    Khandelwal, D., 4 Mar 2020, Eindhoven: Technische Universiteit Eindhoven. 255 p.

    Research output: ThesisPhd Thesis 1 (Research TU/e / Graduation TU/e)

    Open Access

    Nanometer-accurate motion control of moving-magnet planar motors

    Proimadis, I., 2020, (Accepted/In press) Eindhoven: Technische Universiteit Eindhoven.

    Research output: ThesisPhd Thesis 1 (Research TU/e / Graduation TU/e)

    Active compensation of the deformation of a magnetically levitated mover of a planar motor

    Custers, C., Proimadis, I., Jansen, J. W. H., Butler, H., Toth, R., Lomonova, E. & Van den Hof, P., May 2019, 2019 IEEE International Electric Machines and Drives Conference, IEMDC 2019. Piscataway: Institute of Electrical and Electronics Engineers, p. 854-861 8 p. 8785302

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    Open Access
  • 74 Downloads (Pure)


    • 4 Editorial activity
    • 1 Conference

    ECC (Publisher)

    Maarten Schoukens (Editorial board member)
    2019 → …

    Activity: Publication peer-review and editorial work typesEditorial activityScientific

    IEEE-CSS (Publisher)

    Maarten Schoukens (Editorial board member)
    2019 → …

    Activity: Publication peer-review and editorial work typesEditorial activityScientific

    3rd IFAC Workshop on Linear Parameter-Varying Systems

    Maarten Schoukens (Organiser)

    Activity: Participating in or organising an event typesConferenceScientific

    Student theses

    Advanced adaptive space discretization for special element method applied to electromechanical devices

    Author: Geerlofs, M., 30 Aug 2018

    Supervisor: Lomonova, E. (Supervisor 1), Wijnands, K. (Supervisor 2), Krop, D. (Supervisor 2), Toth, R. (Supervisor 2) & Curti, M. (Supervisor 2)

    Student thesis: Master

    Linear parameter varying control of nonlinear systems

    Author: Sharif, B., 30 Aug 2018

    Supervisor: Toth, R. (Supervisor 1) & Mazzoccante, G. S. (Supervisor 2)

    Student thesis: Master

    Nonlinear tracking and rejection using linear parameter-varying control

    Author: Koelewijn, P., 2018

    Supervisor: Toth, R. (Supervisor 1)

    Student thesis: Master