Projects per year
Pepijn Cox was born on 12th January 1989 in Arnhem, The Netherlands. He has received his B.Sc. degree in Mechanical Engineering with distinction in 2010 and his M.Sc. degree in Systems and Control Engineering with distinction in 2013, both at the Delft University of Technology, the Netherlands. His M.Sc. topic was on “Verification of Cascading Events in Interconnected Stochastic Systems: Using Adaptive Parametric Importance Sampling Method”.
In 2013, he started his Ph.D. project at the Control Systems group at Eindhoven University of Technology (TU/e), The Netherlands. His Ph.D. topic was "Towards Efficient Identification of Linear Parameter-Varying State-Space Models" under the supervision of prof.dr.ir. P.M.J. Van den Hof and dr.ir. R. Tóth. During the period 2013-2014, he took graduate courses at the Dutch Institute of Systems and Control (DISC) and received the DISC certificate. Currently, he is a postdoctoral researcher in the Control Systems group at TU/e. Pepijn Cox’s main research interests are in linear parameter-varying (LPV) and nonlinear system modelling and identification.
Cox, P. B. & Tóth, R., Jan 2021, In : Automatica. 123, 14 p., 109296.
Research output: Contribution to journal › Article › Academic › peer-reviewOpen AccessFile7 Downloads (Pure)
Cox, P. B., Weiland, S. & Toth, R., 1 Nov 2018, In : IEEE Transactions on Automatic Control. 63, 11, p. 3865-3872 8 p., 8334291.
Research output: Contribution to journal › Article › Academic › peer-reviewOpen AccessFile91 Downloads (Pure)
LPV state-space identification via IO methods and efficient model order reduction in comparison with subspace methodsSchulz, E., Cox, P. B., Toth, R. & Werner, H., 18 Jan 2018, 2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017. Piscataway: Institute of Electrical and Electronics Engineers, Vol. 2018-January. p. 3575-3581 7 p.
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review1 Citation (Scopus)1 Downloads (Pure)
Prediction-error identification of LPV systems : a nonparametric Gaussian regression approach: A nonparametric Gaussian regression approachDarwish, M. A. H., Cox, P. B., Proimadis, I., Pillonetto, G. & Toth, R., Nov 2018, In : Automatica. 97, p. 92-103 12 p.
Research output: Contribution to journal › Article › Academic › peer-review
Cox, P. B., 20 Mar 2018, Eindhoven: Technische Universiteit Eindhoven. 341 p.
Research output: Thesis › Phd Thesis 1 (Research TU/e / Graduation TU/e)Open AccessFile925 Downloads (Pure)