Dynamic Networks: Data-Driven Modeling and Control
We develop methods and tools for the modeling of dynamic networks on the basis of operational data, to be used as a basis for model-based operations as surveillance, detection, monitoring and control.
Research Profile
Demands on engineering systems require the ability to monitor and optimize the behavior of dynamic systems that are interconnected as networks of systems. We develop methods and tools for the modeling of dynamic networks on the basis of operational data, to be used as a basis for model-based operations as surveillance, detection, monitoring and control. For this purpose we build on contributions from the fields of system identification, machine learning, data science and dynamic systems & control. Potential domains of applications include distributed (smart) power systems, industrial production processes, transportation networks and high-tech mechatronic systems.
Meet some of our Researchers
Most important project
ERC Advanced Research Project - Data-Driven Modeling in Dynamic Networks https://www.sysdynet.eu/
Recent Publications
Our most recent peer reviewed publications
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Lucian Cristian Iacob,Roland Tóth,Maarten Schoukens
Koopman form of nonlinear systems with inputs
Automatica (2024) -
Mircea Lazar,Maarten Schoukens
Nonlinear Data-Driven Predictive Control Using Deep Subspace Prediction Networks
(2024) -
Jan H. Hoekstra,Bence Cseppentő,G.I. Beintema,Maarten Schoukens,Zsolt Kollár,Roland Tóth
Computationally efficient predictive control based on ANN state-space model
(2024) -
Jin Song Pei,Koos van Berkel,Maarten Schoukens
Identification of structured nonlinear state–space models for hysteretic systems using neural network hysteresis operators
Measurement: Journal of the International Measurement Confederation (2024) -
Paul M.J. Van den Hof,Karthik R. Ramaswamy,Stefanie J.M. Fonken
Integrating data-informativity conditions in predictor models for single module identification in dynamic networks
IFAC-PapersOnLine (2023)
Contact
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Visiting address
FluxGroene Loper 195612 AP EindhovenNetherlands -
Visiting address
FluxGroene Loper 195612 AP EindhovenNetherlands -
Postal address
P.O. Box 513Department of Electrical Engineering5600 MB EindhovenNetherlands -
Postal address
P.O. Box 513Department of Electrical Engineering5600 MB EindhovenNetherlands