activity
20182026
most citedTowards a Scalable and Flexible Simulation and Testing Environment Toolbox for Intelligent Microgrid Control

4 citations · 7 across the 5 of their papers we have counts for

collaborators

10 papers

eess.SY2026

A Power Electronic Converter Control Framework Based on Graph Neural Networks -- An Early Proof-of-Concept

Darius Jakobeit, Oliver Wallscheid

Power electronic converter control is typically tuned per topology, limiting transfer across heterogeneous designs. This letter proposes a topology-agnostic meta-control framework…

eess.SY20221 cited

Steady-State Error Compensation in Reference Tracking and Disturbance Rejection Problems for Reinforcement Learning-Based Control

Daniel Weber, Maximilian Schenke, Oliver Wallscheid

Reinforcement learning (RL) is a promising, upcoming topic in automatic control applications. Where classical control approaches require a priori system knowledge, data-driven cont…

cs.LG2021

Improved Exploring Starts by Kernel Density Estimation-Based State-Space Coverage Acceleration in Reinforcement Learning

Maximilian Schenke, Oliver Wallscheid

Reinforcement learning (RL) is currently a popular research topic in control engineering and has the potential to make its way to industrial and commercial applications. Correspond…

eess.SY20204 cited

Towards a Scalable and Flexible Simulation and Testing Environment Toolbox for Intelligent Microgrid Control

Henrik Bode, Stefan Heid, Daniel Weber +2

Micro- and smart grids (MSG) play an important role both for integrating renewable energy sources in conventional electricity grids and for providing power supply in remote areas.…

eess.SY2020

Data Set Description: Identifying the Physics Behind an Electric Motor -- Data-Driven Learning of the Electrical Behavior (Part I)

Sören Hanke, Oliver Wallscheid, Joachim Böcker

Two of the most important aspects of electric vehicles are their efficiency or achievable range. In order to achieve high efficiency and thus a long range, it is essential to avoid…

eess.SY2020

Data Set Description: Identifying the Physics Behind an Electric Motor -- Data-Driven Learning of the Electrical Behavior (Part II)

Sören Hanke, Oliver Wallscheid, Joachim Böcker

A data set was recorded to evaluate different methods for extracting mathematical models for a three-phase permanent magnet synchronous motor (PMSM) and a two-level IGBT inverter f…