16 citations · 73 across the 34 of their papers we have counts for
38 papers
Event-triggered Control and Online Learning for Networked Systems under Computational Delays
Xiaobing Dai, Armin Lederer, Zewen Yang +4
Online learning-based control is a promising approach to control uncertain systems, where unknown components are identified during operation to improve control performance. However…
Koopman operator theory: fundamentals, control, and applications
Igor Mezić, Jorge Cortés, Karl Worthmann +2
The Koopman operator has gained considerable attention due to its ability to provide a global linear representation of highly complex dynamical systems. The operator describes nonl…
Dynamic Neural Koopman Distillation for Fast Robot Control Using Diffusion Models
Lei Zheng, Peiqi Yu, Zengqi Peng +2
Diffusion models excel at generating diverse, multimodal trajectories for robotic control, yet their iterative denoising process introduces latency that can constrain real-time clo…
On the Existence of Quadratic Control Lyapunov Functions for Koopman-Operator based Bilinear Systems
Sami Leon Noel Aziz Hanna, Nicolas Hoischen, Sandra Hirche +1
Koopman operator-based methods enable data-driven bilinear representations of unknown nonlinear control systems. Accurate representations often demand significantly higher dimensio…
SAD-Flower: Flow Matching for Safe, Admissible, and Dynamically Consistent Planning
Tzu-Yuan Huang, Armin Lederer, Dai-Jie Wu +6
Flow matching (FM) has shown promising results in data-driven planning. However, it inherently lacks formal guarantees for ensuring state and action constraints, whose satisfaction…
Koopman-Equivariant Gaussian Processes
Petar Bevanda, Max Beier, Armin Lederer +3
Credible forecasting and representation learning of dynamical systems are of ever-increasing importance for reliable decision-making. To that end, we propose a family of Gaussian p…