Enabling smart, high-performance operation of technical systems across technology domains
The mission of the group is to be an internationally recognized centre of research in systems and control, where contributions to fundamental theory are combined with advancing innovative technological applications in a selected number of domains, in cooperation with relevant industrial partners. The fundamental research of CS is directed towards the following research lines:
• Data-driven modelling in dynamic networks
• Modelling and control of linear parameter varying systems
• Spatial-temporal multi-physics systems and model reduction
• Data analytics and machine learning
• Constrained and interconnected systems
• Model-based control and optimization
• Control of cyber-physical systems
Our Labs
Work with us!
All scientific as well as non-scientific vacancies are centrally cataloged by the Electrical Engineering department and can be found here.
CURRENT OPEN POSITION
PostDoc on Model learning in dynamic networks (1 year + 1 year)
Meet some of our Researchers
Innovation
Control Systems has four main application domains: High Tech Systems, Automotive, Process industry and Energy. In each of these domains CS collaborates with leading companies contributing our fundamental knowledge to their innovation roadmaps. Often these companies are dominant market players, sometimes world leaders. With most of them CS has already built up a relationship over many years.
Below you can find the listing of most of our industry partners, a description of the innovation topics and a link to project details.
Some of our projects
News






Recent Publications
Our most recent peer reviewed publications
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Convex incremental dissipativity analysis of nonlinear systems
Automatica (2023) -
Fast simultaneous estimation of nD transport coefficients and source function in perturbation experiments
Scientific Reports (2023) -
On the informativity of direct identification experiments in dynamical networks
Automatica (2023) -
Globally Stabilizing Triangularly Angle Rigid Formations
IEEE Transactions on Automatic Control (2023) -
Message passing-based system identification for NARMAX models
(2023)
Contact
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Visiting address
FluxGroene Loper 195612 AP EindhovenNetherlands -
Postal address
P.O. Box 513Department of Electrical Engineering5600 MB EindhovenNetherlands -
Secretarysecretariaat.CS@ tue.nl