258 citations · 1.2k across the 64 of their papers we have counts for
9 papers · 1 filter
Data-efficient Auto-tuning with Bayesian Optimization: An Industrial Control Study
Matthias Neumann-Brosig, Alonso Marco, Dieter Schwarzmann +1
Bayesian optimization is proposed for automatic learning of optimal controller parameters from experimental data. A probabilistic description (a Gaussian process) is used to model…
Deep Reinforcement Learning for Event-Triggered Control
Dominik Baumann, Jia-Jie Zhu, Georg Martius +1
Event-triggered control (ETC) methods can achieve high-performance control with a significantly lower number of samples compared to usual, time-triggered methods. These frameworks…
Gait learning for soft microrobots controlled by light fields
Alexander von Rohr, Sebastian Trimpe, Alonso Marco +2
Soft microrobots based on photoresponsive materials and controlled by light fields can generate a variety of different gaits. This inherent flexibility can be exploited to maximize…
Learning an Approximate Model Predictive Controller with Guarantees
Michael Hertneck, Johannes Köhler, Sebastian Trimpe +1
A supervised learning framework is proposed to approximate a model predictive controller (MPC) with reduced computational complexity and guarantees on stability and constraint sati…
A Local Information Criterion for Dynamical Systems
Arash Mehrjou, Friedrich Solowjow, Sebastian Trimpe +1
Encoding a sequence of observations is an essential task with many applications. The encoding can become highly efficient when the observations are generated by a dynamical system.…
Efficient Encoding of Dynamical Systems through Local Approximations
Friedrich Solowjow, Arash Mehrjou, Bernhard Schölkopf +1
An efficient representation of observed data has many benefits in various domains of engineering and science. Representing static data sets, such as images, is a living branch in m…
Evaluating Low-Power Wireless Cyber-Physical Systems
Dominik Baumann, Fabian Mager, Harsoveet Singh +2
Simulation tools and testbeds have been proposed to assess the performance of control designs and wireless protocols in isolation. A cyber-physical system (CPS), however, integrate…
Feedback Control Goes Wireless: Guaranteed Stability over Low-power Multi-hop Networks
Fabian Mager, Dominik Baumann, Romain Jacob +3
Closing feedback loops fast and over long distances is key to emerging applications; for example, robot motion control and swarm coordination require update intervals of tens of mi…
Event-triggered Learning for Resource-efficient Networked Control
Friedrich Solowjow, Dominik Baumann, Jochen Garcke +1
Common event-triggered state estimation (ETSE) algorithms save communication in networked control systems by predicting agents' behavior, and transmitting updates only when the pre…