Research Profile
We make use of model predictive control (MPC) theory to deal with constraints and we design MPC algorithms and fast MPC solvers for complex systems (highly nonlinear, hybrid, uncertain or large-scale interconnected systems). We research flexible control Lyapunov functions to enforce stability for real-time controllers. To increase autonomy and reliability of control systems we focus on integration of artificial intelligence (neural networks) with classical and predictive controllers.
Read moreProjects
Meet some of our Researchers
Most important active projects
- HTSM TTW-NWO grant: Embedded power electronics, converters and control (in collaboration with Prof. Elena Lomonova, EPE, Electrical Engineering, TU/e)
- EU H2020 project: Implementation of powertrain control for economic, low real driving emissions and fuel consumption (Imperium, in collaboration with Dr. John Kessels, DAF)
Recent Publications
Our most recent peer reviewed publications
-
On a canonical distributed controller in the behavioral framework
Systems and Control Letters (2023) -
Generalized Data–Driven Predictive Control
Mathematics (2023) -
Physics–Guided Neural Networks for Feedforward Control
(2023) -
Offset–free data–driven predictive control
(2023) -
Recursive data–driven predictive control with persistence of excitation conditions
(2023)
Contact
-
Visiting address
Joey van Laar LLBFluxGroene Loper 195612 AP EindhovenNetherlandsdina.debruijn@ gmail.com -
Visiting address
Boris van Bovenendrs Levi van der VeldeJanssenboulevard3551GH KerkwijkNetherlandsschrik.amelie@ kok.nl -
Postal address
ir. Jaylinn van Kuijc van Malsen MPhilP.O. Box 513Department of Electrical Engineering5600 MB EindhovenNetherlandsvanvliet.jolijn@ gmail.com -
Postal address
Giel Schipperdr. Anouk de Boer LLMde Witdreef7273PP MiddelaarNetherlandsyyavuz@ vantuijl.nl