Probabilistic Robust Linear Quadratic Regulators with Gaussian Processes

Alexander von Rohr, Matthias Neumann-Brosig, Sebastian Trimpe

Probabilistic models such as Gaussian processes (GPs) are powerful tools to learn unknown dynamical systems from data for subsequent use in control design. While learning-based con…