16 citations · 73 across the 34 of their papers we have counts for
16 papers · 1 filter
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…
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…
Toward Near-Globally Optimal Nonlinear Model Predictive Control via Diffusion Models
Tzu-Yuan Huang, Armin Lederer, Nicolas Hoischen +4
Achieving global optimality in nonlinear model predictive control (NMPC) is challenging due to the non-convex nature of the underlying optimization problem. Since commonly employed…
Safe Event-triggered Gaussian Process Learning for Barrier-Constrained Control
Armin Lederer, Azra Begzadić, Sandra Hirche +2
While control barrier functions (CBFs) are employed in addressing safety, control synthesis methods based on them generally rely on accurate system dynamics. This is a critical lim…
Stable Inverse Reinforcement Learning: Policies from Control Lyapunov Landscapes
Samuel Tesfazgi, Leonhard Sprandl, Armin Lederer +1
Learning from expert demonstrations to flexibly program an autonomous system with complex behaviors or to predict an agent's behavior is a powerful tool, especially in collaborativ…
Risk-Sensitive Inhibitory Control for Safe Reinforcement Learning
Armin Lederer, Erfaun Noorani, John S. Baras +1
Humans have the ability to deviate from their natural behavior when necessary, which is a cognitive process called response inhibition. Similar approaches have independently receiv…