5 citations · 13 across the 6 of their papers we have counts for
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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…
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…
An Online Adaptation Strategy for Direct Data-driven Control
Johannes Teutsch, Sebastian Ellmaier, Sebastian Kerz +2
The fundamental lemma from behavioral systems theory yields a data-driven non-parametric system representation that has shown great potential for the data-efficient control of unkn…
Offline Uncertainty Sampling in Data-driven Stochastic MPC
Johannes Teutsch, Sebastian Kerz, Tim Brüdigam +2
In this work, we exploit an offline-sampling based strategy for the constrained data-driven predictive control of an unknown linear system subject to random measurement noise. The…
Data-driven tube-based stochastic predictive control
Sebastian Kerz, Johannes Teutsch, Tim Brüdigam +2
A powerful result from behavioral systems theory known as the fundamental lemma allows for predictive control akin to Model Predictive Control (MPC) for linear time invariant (LTI)…