4 citations · 11 across the 9 of their papers we have counts for
5 papers · 1 filter
Adaptive Stochastic Predictive Control from Noisy Data: A Sampling-based Approach
Johannes Teutsch, Christopher Narr, Sebastian Kerz +2
In this work, an adaptive predictive control scheme for linear systems with unknown parameters and bounded additive disturbances is proposed. In contrast to related adaptive contro…
Safe and Non-Conservative Trajectory Planning for Autonomous Driving Handling Unanticipated Behaviors of Traffic Participants
Tommaso Benciolini, Michael Fink, Nehir Güzelkaya +2
Trajectory planning for autonomous driving is challenging because the unknown future motion of traffic participants must be accounted for, yielding large uncertainty. Stochastic Mo…
Minimal Constraint Violation Probability in Model Predictive Control for Linear Systems
Michael Fink, Tim Brüdigam, Dirk Wollherr +1
Handling uncertainty in model predictive control comes with various challenges, especially when considering state constraints under uncertainty. Most methods focus on either the co…
Combining Belief Function Theory and Stochastic Model Predictive Control for Multi-Modal Uncertainty in Autonomous Driving
Tommaso Benciolini, Yuntian Yan, Dirk Wollherr +1
In automated driving, predicting and accommodating the uncertain future motion of other traffic participants is challenging, especially in unstructured environments in which the hi…
Sampling-based Stochastic Data-driven Predictive Control under Data Uncertainty - Extended Version
Johannes Teutsch, Sebastian Kerz, Dirk Wollherr +1
We present a stochastic constrained output-feedback data-driven predictive control scheme for linear time-invariant systems subject to bounded additive disturbances. The approach u…