Research
I am largely interested in dynamical problems, e.g., designing (optimization) algorithms and control systems.
In particular, I like to understand the interplay between the underlying problem structure and achievable qualitative behaviour.
Selected (pre)prints
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On topological properties of compact attractors on Hausdorff spaces
Wouter Jongeneel
submitted 2023.
|pdf| |arXiv| |bibtex|
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A Large Deviations Perspective on Policy Gradient Algorithms
Mengmeng Li, Wouter Jongeneel and Daniel Kuhn
2023.
|arXiv|
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Topological Obstructions to Stability and Stabilization: History, Recent Advances and Open Problems
Wouter Jongeneel and Emmanuel Moulay
SpringerBriefs in Control, Automation and Robotics (Open Access), pp. X, 132, 2023.
|pdf| |link (Springer)| |Supported by the SNSF|
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On continuation and convex Lyapunov functions
Wouter Jongeneel and Roland Schwan
submitted 2023.
|pdf| |arXiv| |bibtex|
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Topological Linear System Identification via Moderate Deviations Theory
Wouter Jongeneel, Tobias Sutter and Daniel Kuhn
IEEE Control Systems Letters, vol. 6, pp. 307-312, 2022.
Presented at the 2021 CDC
|arXiv| |link (IEEE)| |bibtex|
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Robust Linear Quadratic Regulator: Exact Tractable Reformulation
Wouter Jongeneel, Tyler Summers and Peyman Mohajerin Esfahani
IEEE Conference on Decision and Control (CDC), pp. 6742 - 6747, 2019.
|pdf| |link (IEEE)| |bibtex|
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With special thanks to Daniel Kuhn, Mengmeng Li, Peyman Mohajerin Esfahani, Emmanuel Moulay, Roland Schwan, Tyler Summers, Tobias Sutter and Man-Chung Yue.
Selected talks (feel free to request slides or references, I aim to put everything online)
Topological obstructions to stability and stabilization, March 2022, University of Warsaw, Department of Mathematical Methods in Physics, Theory of Duality seminar.
From Correlated Data to Guarantees in Stable Identification, October 2020, ETH Zürich, Institut für Automatik (IfA).
Other
Stability via reverse I-projections, a symplectic perspective on the computation
Wouter Jongeneel
technical note, 2022
|pdf|
From Moderate Deviations Theory to Distributionally Robust Optimization: Learning from Correlated Data
Tobias Sutter, Wouter Jongeneel and Daniel Kuhn
|video at SPS|
Thesis
Controlling the Unknown: A Game Theoretic Perspective
Wouter Jongeneel
MSc. Thesis, Systems & Control, Delft University of Technology (TU Delft) 2019, adviser Peyman Mohajerin Esfahani.
|pdf| |link| |bibtex|
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