1 citations · 1 across the 2 of their papers we have counts for
5 papers
Efficient Uniform Feasible-Set Sampling for Approximate Linear MPC
Elias Milios, Felix Berkel, Felix Gruber +2
Model Predictive Control (MPC) offers safe and near-optimal control but suffers from high computational costs. Approximate MPC (AMPC) mitigates this by learning a cheaper surrogate…
Tunable Real-Time Safety Filters via Set-Based Control Barrier Functions
Kim P. Wabersich, Felix Berkel, Felix Gruber +1
Safety filters for industrial constrained systems are required to combine certified constraint satisfaction, predictable online computation, and a transparent tuning interface. Exi…
Contract-based hierarchical control using predictive feasibility value functions
Felix Berkel, Kim Peter Wabersich, Hongxi Xiang +1
Today's control systems are often characterized by modularity and safety requirements to handle complexity, resulting in the use of hierarchical control structures. Although hierar…
Stability Mechanisms for Predictive Safety Filters
Elias Milios, Kim Peter Wabersich, Felix Berkel +1
Predictive safety filters enable the integration of potentially unsafe learning-based control approaches and humans into safety-critical systems. In addition to simple constraint s…
Vehicle single track modeling using physics guided neural differential equations
Stephan Rhode, Fabian Jarmolowitz, Felix Berkel
In this paper, we follow the physics guided modeling approach and integrate a neural differential equation network into the physical structure of a vehicle single track model. By r…