activity
20092022
most citedFlexible development and evaluation of machine-learning-supported optimal control and estimation methods via HILO-MPC

10 citations · 11 across the 7 of their papers we have counts for

collaborators

13 papers

eess.SY20221 cited

Safe Hierarchical Model Predictive Control and Planning for Autonomous Systems

Markus Koegel, Mohamed Ibrahim, Christian Kallies +1

Planning and control for autonomous vehicles usually are hierarchical separated. However, increasing performance demands and operating in highly dynamic environments requires an fr…

eess.SY202210 cited

Flexible development and evaluation of machine-learning-supported optimal control and estimation methods via HILO-MPC

Johannes Pohlodek, Bruno Morabito, Christian Schlauch +2

Model-based optimization approaches for monitoring and control, such as model predictive control and optimal state and parameter estimation, have been used for decades in many engi…

eess.SY2021

Control of Scanning Quantum Dot Microscopy

Michael Maiworm, Christian Wagner, Taner Esat +4

Scanning quantum dot microscopy is a recently developed high-resolution microscopy technique that is based on atomic force microscopy and is capable of imaging the electrostatic po…

eess.SY2021

A Polynomial Chaos Approach to Robust Static Output-Feedback Control with Bounded Truncation Error

Yiming Wan, Dongying E. Shen, Sergio Lucia +2

This article considers the static output-feedback control for linear time-invariant uncertain systems with polynomial dependence on probabilistic time-invarian…

eess.SY2020

Controller tuning in power systems using singular value optimization

Amer Mešanović, Ulrich Münz, Rolf Findeisen

As the share of renewable generation in large power systems continues to increase, the operation of power systems becomes increasingly challenging. The constantly shifting mix of r…

eess.SY2020

Fusing Online Gaussian Process-Based Learning and Control for Scanning Quantum Dot Microscopy

Maik Pfefferkorn, Michael Maiworm, Christian Wagner +2

Elucidating electrostatic surface potentials contributes to a deeper understanding of the nature of matter and its physicochemical properties, which is the basis for a wide field o…