571 citations · 1.3k across the 123 of their papers we have counts for
11 papers · 1 filter
System Level Disturbance Reachable Sets and their Application to Tube-based MPC
Jerome Sieber, Andrea Zanelli, Samir Bennani +1
Tube-based model predictive control (MPC) methods leverage tubes to bound deviations from a nominal trajectory due to uncertainties in order to ensure constraint satisfaction. This…
Stability and performance analysis of NMPC: Detectable stage costs and general terminal costs
Johannes Köhler, Melanie N. Zeilinger, Lars Grüne
We provide a stability and performance analysis for nonlinear model predictive control (NMPC) schemes subject to input constraints. Given an exponential stabilizability and detecta…
On-Policy Model Errors in Reinforcement Learning
Lukas P. Fröhlich, Maksym Lefarov, Melanie N. Zeilinger +1
Model-free reinforcement learning algorithms can compute policy gradients given sampled environment transitions, but require large amounts of data. In contrast, model-based methods…
Contextual Tuning of Model Predictive Control for Autonomous Racing
Lukas P. Fröhlich, Christian Küttel, Elena Arcari +3
Learning-based model predictive control has been widely applied in autonomous racing to improve the closed-loop behaviour of vehicles in a data-driven manner. When environmental co…
Adaptive Model Predictive Safety Certification for Learning-based Control -- Extended Version
Alexandre Didier, Kim P. Wabersich, Melanie N. Zeilinger
We propose an adaptive Model Predictive Safety Certification (MPSC) scheme for learning-based control of linear systems with bounded disturbances and uncertain parameters where the…
Learning-based Moving Horizon Estimation through Differentiable Convex Optimization Layers
Simon Muntwiler, Kim P. Wabersich, Melanie N. Zeilinger
To control a dynamical system it is essential to obtain an accurate estimate of the current system state based on uncertain sensor measurements and existing system knowledge. An op…
Predictive control barrier functions: Enhanced safety mechanisms for learning-based control
Kim P. Wabersich, Melanie N. Zeilinger
While learning-based control techniques often outperform classical controller designs, safety requirements limit the acceptance of such methods in many applications. Recent develop…
A System Level Approach to Tube-based Model Predictive Control
Jerome Sieber, Samir Bennani, Melanie N. Zeilinger
Robust tube-based model predictive control (MPC) methods address constraint satisfaction by leveraging an a priori determined tube controller in the prediction to tighten the const…
Design, Optimal Guidance and Control of a Low-cost Re-usable Electric Model Rocket
Lukas Spannagl, Elias Hampp, Andrea Carron +5
In the last decade, autonomous vertical take-off and landing (VTOL) vehicles have become increasingly important as they lower mission costs thanks to their re-usability. However, t…
Data-driven control of room temperature and bidirectional EV charging using deep reinforcement learning: simulations and experiments
B. Svetozarevic, C. Baumann, S. Muntwiler +3
This work presents a fully data-driven, black-box pipeline to obtain an optimal control policy for a multi-loop building control problem based on historical building and weather da…
A predictive safety filter for learning-based racing control
Ben Tearle, Kim P. Wabersich, Andrea Carron +1
The growing need for high-performance controllers in safety-critical applications like autonomous driving has been motivating the development of formal safety verification techniqu…