7 papers
A model-free approach to control barrier functions for higher-order systems
Lukas Lanza, Johannes Köhler, Dario Dennstädt +2
Control barrier functions (CBFs) are a widely applied modular tool to ensure safe operation of nonlinear dynamical control systems. However, for their construction accurate knowled…
A model-free approach to control barrier functions using funnel control
Lukas Lanza, Johannes Köhler, Dario Dennstädt +2
Control barrier functions (CBFs) are a popular approach to design feedback laws that achieve safety guarantees for nonlinear systems. The CBF-based controller design relies on the…
On Model Predictive Funnel Control with Equilibrium Endpoint Constraints
Jens Göbel, Dario Dennstädt, Lukas Lanza +3
We propose model predictive funnel control, a novel model predictive control (MPC) scheme building upon recent results in funnel control. The latter is a high-gain feedback methodo…
Two-component controller design to safeguard data-driven predictive control
Lea Bold, Lukas Lanza, Karl Worthmann
We design a two-component controller to achieve reference tracking with output constraints - exemplified on systems of relative degree two. One component is a data-driven or learni…
Safe continual learning in model predictive control with prescribed bounds on the tracking error
Lukas Lanza, Dario Dennstädt, Thomas Berger +1
We develop a three-component Model Predictive Control (MPC) algorithm to achieve output-reference tracking with prescribed performance for continuous-time nonlinear systems. One co…
Sampled-data funnel control and its use for safe continual learning
Lukas Lanza, Dario Dennstädt, Karl Worthmann +4
We propose a novel sampled-data output-feedback controller for nonlinear systems of arbitrary relative degree that ensures reference tracking within prescribed error bounds. We pro…