8 citations · 13 across the 12 of their papers we have counts for
6 papers · 2 filters
Inverse Dynamic Games Based on Maximum Entropy Inverse Reinforcement Learning
Jairo Inga, Esther Bischoff, Florian Köpf +1
We consider the inverse problem of dynamic games, where cost function parameters are sought which explain observed behavior of interacting players. Maximum entropy inverse reinforc…
Distributed Frequency Regulation for Heterogeneous Microgrids via Steady State Optimal Control
Lukas Kölsch, Manuel Dupuis, Kirtan Bhatt +2
In this paper, we present a model-based frequency controller for microgrids with nonzero line resistances based on a port-Hamiltonian formulation of the microgrid model and real-ti…
Steady-State Optimal Frequency Control for Lossy Power Grids with Distributed Communication
Lukas Kölsch, Kirtan Bhatt, Stefan Krebs +1
We present a distributed and price-based control approach for frequency regulation in power grids with nonzero line conductances. Both grid and controller are modeled as a port-Ham…
Adaptive Dynamic Programming for Model-free Tracking of Trajectories with Time-varying Parameters
Florian Köpf, Simon Ramsteiner, Michael Flad +1
In order to autonomously learn to control unknown systems optimally w.r.t. an objective function, Adaptive Dynamic Programming (ADP) is well-suited to adapt controllers based on ex…
Partner Approximating Learners (PAL): Simulation-Accelerated Learning with Explicit Partner Modeling in Multi-Agent Domains
Florian Köpf, Alexander Nitsch, Michael Flad +1
Mixed cooperative-competitive control scenarios such as human-machine interaction with individual goals of the interacting partners are very challenging for reinforcement learning…
Adaptive Optimal Control for Reference Tracking Independent of Exo-System Dynamics
Florian Köpf, Johannes Westermann, Michael Flad +1
Model-free control based on the idea of Reinforcement Learning is a promising approach that has recently gained extensive attention. However, Reinforcement-Learning-based control m…