Research Output per year
Personal profile
Research profile
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.
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Identification (control systems)
Engineering & Materials Science
Scheduling
Engineering & Materials Science
Impulse response
Engineering & Materials Science
Maximum likelihood
Engineering & Materials Science
Maximum likelihood estimation
Engineering & Materials Science
Computational complexity
Engineering & Materials Science
Lyapunov functions
Engineering & Materials Science
Nonlinear systems
Engineering & Materials Science
Network
Recent external collaboration on country level. Dive into details by clicking on the dots.
Research Output 2014 2018
Affine parameter-dependent Lyapunov functions for LPV systems with affine dependence
Cox, P. B., Weiland, S. & Toth, R., 1 Nov 2018, In : IEEE Transactions on Automatic Control. 63, 11, p. 3865-3872Research output: Contribution to journal › Article › Academic › peer-review
Open Access
File
Lyapunov functions
Linear matrix inequalities
Linear systems
Robust stability
Uncertainty
LPV state-space identification via IO methods and efficient model order reduction in comparison with subspace methods
Schulz, 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-review
Model Order Reduction
Subspace Methods
Identification (control systems)
State Space
Output
Prediction-error identification of LPV systems : a nonparametric Gaussian regression approach: A nonparametric Gaussian regression approach
Darwish, 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
Controllers
Networked control systems
Scheduling
Batch reactors
Communication
Towards efficient identification of linear parameter-varying state-space models
Cox, P. B., 20 Mar 2018, Eindhoven: Technische Universiteit Eindhoven. 341 p.Research output: Thesis › Phd Thesis 1 (Research TU/e / Graduation TU/e) › Academic
Open Access
File
Identification (control systems)
Gasoline
Engines
Towards efficient maximum likelihood estimation of LPV-SS models
Cox, P. B., Tóth, R. & Petreczky, M., 1 Nov 2018, In : Automatica. 97, p. 392-403 12 p.Research output: Contribution to journal › Article › Academic › peer-review
Open Access
Maximum likelihood estimation
Maximum likelihood
Impulse response
Dynamical systems
Scheduling
Student theses
Sensing and control design for high speed autonomous agile manoeuvring with quad-rotors
Author: Kiriouchine, V., 2018Supervisor: Toth, R. (Supervisor 1), Cox, P. (Supervisor 2) & Steinbuch, M. (Supervisor 2)
Student thesis: Master