Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Utrecht UniversityNL210 papers
- Delft University of TechnologyNL196 papers
- Centre National de la Recherche ScientifiqueFR195 papers
- Centrum Wiskunde & InformaticaNL163 papers
- University of TwenteNL158 papers
- University of AmsterdamNL113 papers
- Radboud University NijmegenNL89 papers
- University of Rome Tor VergataIT84 papers
- Vrije Universiteit AmsterdamNL79 papers
- Leiden UniversityNL72 papers
- University of GroningenNL58 papers
- Philips (Netherlands)NL56 papers
7 papers · 2 filters
Application of the Free Energy Principle to Estimation and Control
Thijs van de Laar, Ayça Özçelikkale, Henk Wymeersch
Based on a generative model (GM) and beliefs over hidden states, the free energy principle (FEP) enables an agent to sense and act by minimizing a free energy bound on Bayesian sur…
Linear Parameter-Varying Control of Nonlinear Systems based on Incremental Stability
P. J. W. Koelewijn, R. Tóth, H. Nijmeijer
The Linear Parameter-Varying (LPV) framework has long been used to guarantee performance and stability requirements of nonlinear (NL) systems mainly through the -gai…
A Comparison of LPV Gain Scheduling and Control Contraction Metrics for Nonlinear Control
Ruigang Wang, Roland Tóth, Ian R. Manchester
Gain-scheduled control based on linear parameter-varying (LPV) models derived from local linearizations is a widespread nonlinear technique for tracking time-varying setpoints. Rec…
On the smoothness of nonlinear system identification
Antônio H. Ribeiro, Koen Tiels, Jack Umenberger +2
We shed new light on the \textit{smoothness} of optimization problems arising in prediction error parameter estimation of linear and nonlinear systems. We show that for regions of…
Data-driven Modelling of Dynamical Systems Using Tree Adjoining Grammar and Genetic Programming
Dhruv Khandelwal, Maarten Schoukens, Roland Tóth
State-of-the-art methods for data-driven modelling of non-linear dynamical systems typically involve interactions with an expert user. In order to partially automate the process of…
Bayesian topology identification of linear dynamic networks
Shengling Shi, Giulio Bottegal, Paul M. J. Van den Hof
In networks of dynamic systems, one challenge is to identify the interconnection structure on the basis of measured signals. Inspired by a Bayesian approach in [1], in this paper,…
Abstractions of linear dynamic networks for input selection in local module identification
Harm H. M. Weerts, Jonas Linder, Martin Enqvist +1
In abstractions of linear dynamic networks, selected node signals are removed from the network, while keeping the remaining node signals invariant. The topology and link dynamics,…