198 citations · 558 across the 21 of their papers we have counts for
5 papers · 1 filter
Constrained Gaussian Process Learning for Model Predictive Control
Janine Matschek, Andreas Himmel, Kai Sundmacher +1
Many control tasks can be formulated as a tracking problem of a known or unknown reference signal. Examples are movement compensation in collaborative robotics, the synchronisation…
Learning References with Gaussian Processes in Model Predictive Control applied to Robot Assisted Surgery
Janine Matschek, Tim Gonschorek, Magnus Hanses +3
One of the key benefits of model predictive control is the capability of controlling a system proactively in the sense of taking the future system evolution into account. However,…
Scalable and Data Privacy Conserving Controller Tuning for Large-Scale Power Networks
Amer Mešanović, Ulrich Münz, Rolf Findeisen
The increasing share of renewable generation leads to new challenges in reliable power system operation, such as the rising volatility of power generation, which leads to time-vary…
Online learning-based Model Predictive Control with Gaussian Process Models and Stability Guarantees
Michael Maiworm, Daniel Limon, Rolf Findeisen
Model predictive control allows to provide high performance and safety guarantees in the form of constraint satisfaction. These properties, however, can be satisfied only if the un…
Structured Controller Parameter Tuning for Power Systems
A. Mesanovic, U. Münz, A. Szabo +6
Reliable and secure operation of power systems becomes increasingly challenging as the share of volatile generation rises, leading to largely changing dynamics. Typically, the arch…