We want an internationally leading role in research, combined with inspiring education, valorisation through spin-off companies, and direct co-operation with industry.
Our overall research strategy is focused on performance-driven design and control. The performance of a controlled system is defined as the extent to which the actual behaviour of the system matches the intended behaviour, while being subject to disturbances acting on the system and variations in system dynamics. Performance requirements can be related, for instance, to the accurate tracking of a set-point (motion) or to the energy utilisation (hybrid vehicles). Fundamental properties that determine and possibly limit performance can be found in both external sources (disturbances acting on the system) and internal sources (system properties, controller properties, quality of sensors and actuators etc.). Only by an integrated design of both the mechatronic (hardware) system and the (software) controller the highest performance requirements can be achieved.
Read moreResearch lines
The research in our group is structured in 6 research lines. Click on the following links to learn more about each topic.
RESEARCH GROUPS
The following research groups are present within the Control Systems Technology section.
Our laboratories
The Control Systems Technology group shares the following laboratory facilities in the Mechanical Engineering Department.
Professors
Associate Professors
Assistant Professors & Lecturers
Part Time Faculty
RESEARCHERS & POST-DOCS
PhD en engD
SUPPORT STAFF
Recent Publications
Our most recent peer reviewed publications
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A Bayesian optimization framework for the automatic tuning of MPC-based shared controllers
(2024) -
Demonstration of a sparse sensor placement technique to the limited diagnostic set in a fusion power plant
Fusion Engineering and Design (2024) -
Reset-Free Data-Driven Gain Estimation
Automatica (2024) -
Automatic patient-ventilator asynchrony detection framework using objective asynchrony definitions
IFAC Journal of Systems and Control (2024) -
Control-relevant neural networks for feedforward control with preview
IFAC Journal of Systems and Control (2024)
Contact
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Postal address
P.O. Box 5135600 MB EindhovenNetherlands -
Postal address
Postbus 5135600 MB EindhovenNetherlands -
Secretarycst@ tue.nl