Guillaume Crevecoeur (1981) received the MSc and the PhD degree in Engineering Physics from Ghent University in 2004 and 2009, respectively. In 2004 he joined the Department of Electrical Energy, Metals, Mechanical Constructions, and Systems as doctoral student and in 2009 he became a postdoctoral fellow of the Research Foundation Flanders (FWO-Flanders). In the winter 2011 he was a visiting researcher at the Technical University Ilmenau and the Physikalische Technische Bundesanstalt, Berlin, Germany. In 2014 he was appointed Associate Professor at the Faculty of Engineering and Architecture of Ghent University. He is furthermore an affiliate member of Flanders Make, the strategic research center for the manufacturing industry, and member within international scientific steering committees. His research interests are the modelling, optimization and control of dynamical systems including foundational work on model-based optimization algorithms, inverse problems and nonlinear optimal control with on-going strategic research on machines and motion systems.
Keywords: Dynamical systems, Machine intelligence, Nonlinear optimal control, Machines and motion systems, System identification
S. Khatiry, K. Dekemele, L. Dupré, M. Loccufier, G. Crevecoeur, “Sparse identification of nonlinear duffing oscillator from measurement data,” 5th IFAC Conference on Analysis and Control of Chaotic Systems, 2018.
T. Lefebvre, F. De Belie, G. Crevecoeur, “Polynomial Chaos reformulation in nonlinear stochastic optimal control with application on a drivetrain subject to bifurcation phenomena,” 22nd International Conference on System Theory, Control and Computing, 2018. (best paper award)
A. De Keyser, H. Vansompel, and G. Crevecoeur, “Adaptive convex loss mappings for enhanced loss assessment in asynchronous drives,” IEEE Transactions on Control Systems Technology, doi: 10.1109/tcst.2018.2843331, 2018.
T. Lefebvre, F. De Belie, and G. Crevecoeur, “A trajectory-based sampling strategy for sequentially refined metamodel management of metamodel-based dynamic optimization in mechatronics,” Optimal Control Applications & Methods, vol. 29, no. 5, pp. 1786-1801, 2017.
G. Crevecoeur, R. De Staelen, “On cost function transformations for the reduction of uncertain model parameters’ impact towards the optimal solutions,” Journal of Computational and Applied Mathematics, vol. 289, pp. 392—399, 2015.