Chris Verhoek
Department / Institute
RESEARCH PROFILE
Chris Verhoek is a Doctoral Candidate at the Control Systems (CS) Group at the Department of Electrical Engineering. His current research is on Learning-Based Control with Stability and Performance Guarantees, under the supervision of Associate Professor Roland Tóth in the AI4GNC (Artificial intelligence techniques for GNC design, implementation, and verification) project in cooperation with SENER and the OSIP (Open Space Innovation Platform) project in cooperation with the European Space Agency (ESA). His main research interests include analysis and control of nonlinear and LPV systems, optimal and nonlinear control, and learning-for-control techniques.
ACADEMIC BACKGROUND
Chris Verhoek obtained his BSc degree in Mechatronics from the Avans University of Applied Sciences Breda in 2017, and his MSc degree in Systems and Control from the Eindhoven University of Technology (TU/e), cum laude, in 2020. During his MSc research, he worked on incremental dissipativity analysis and control of nonlinear systems and on a performance shaping framework for nonlinear systems. His MSc research was carried out in the Control Systems group at the TU/e, under supervision of Associate Professor Roland Tóth. After his MSc graduation he worked for 6 months as a University Researcher in the Control Systems Group at Eindhoven University of Technology, prior to his PhD trajectory that started in February 2021.
Recent Publications
-
C. Verhoek,Sofie Haesaert,Roland Tóth
Another note on persistency of excitation
(2023) -
C. Verhoek,Patrick J.W. Koelewijn,Sofie Haesaert,Roland Tóth
Convex incremental dissipativity analysis of nonlinear systems
Automatica (2023) -
Chris Verhoek,Gerben I. Beintema,Sofie Haesaert,Maarten Schoukens,Roland Tóth
Deep-Learning-Based Identification of LPV Models for Nonlinear Systems
(2023) -
Chris Verhoek,Valentin Preda,Roland Tóth
LPV Modeling of the Atmospheric Flight Dynamics of a Generic Parafoil Return Vehicle
IFAC-PapersOnLine (2022) -
C. Verhoek,G.I. Beintema,Sofie Haesaert,Maarten Schoukens,Roland Tóth
Learning-Based Model-Augmentation of Nonlinear Approximative Models using the Sub-Space Encoder
(2022)
Ancillary Activities
No ancillary activities