206 citations · 207 across the 8 of their papers we have counts for
8 papers
Gain-Scheduling Data-Enabled Predictive Control for Nonlinear Systems with Linearized Operating Regions
Sebastian Zieglmeier, Mathias Hudoba de Badyn, Narada D. Warakagoda +2
This paper presents a Gain-Scheduled Data-Enabled Predictive Control (GS-DeePC) framework for nonlinear systems based on multiple locally linear data representations. Instead of re…
Multi-Horizon Time Series Forecasting of non-parametric CDFs with Deep Lattice Networks
Niklas Erdmann, Lars Bentsen, Roy Stenbro +3
Probabilistic forecasting is not only a way to add more information to a prediction of the future, but it also builds on weaknesses in point prediction. Sudden changes in a time se…
Reinforcement Learning for Pollution Detection in a Randomized, Sparse and Nonstationary Environment with an Autonomous Underwater Vehicle
Sebastian Zieglmeier, Niklas Erdmann, Narada D. Warakagoda
Reinforcement learning (RL) algorithms are designed to optimize problem-solving by learning actions that maximize rewards, a task that becomes particularly challenging in random an…
Data-Enabled Predictive Control with Predictive Adaptive Line-of-Sight Guidance for 3-D Path Following of Autonomous Underwater Vehicles
Sebastian Zieglmeier, Mathias Hudoba de Badyn, Narada D. Warakagoda +2
This paper presents a fully data-driven 3-D path-following framework for autonomous underwater vehicles (AUVs), a representative class of underwater field robotics, based on Data-E…
Semi-Data-Driven Model Predictive Control: A Physics-Informed Data-Driven Control Approach
Sebastian Zieglmeier, Mathias Hudoba de Badyn, Narada D. Warakagoda +2
Data-enabled predictive control (DeePC) has emerged as a powerful technique to control complex systems without the need for extensive modeling efforts. However, relying solely on o…
Deep and Probabilistic Solar Irradiance Forecast at the Arctic Circle
Niklas Erdmann, Lars Ø. Bentsen, Roy Stenbro +3
Solar irradiance forecasts can be dynamic and unreliable due to changing weather conditions. Near the Arctic circle, this also translates into a distinct set of further challenges.…
It is all Connected: A New Graph Formulation for Spatio-Temporal Forecasting
Lars Ødegaard Bentsen, Narada Dilp Warakagoda, Roy Stenbro +1
With an ever-increasing number of sensors in modern society, spatio-temporal time series forecasting has become a de facto tool to make informed decisions about the future. Most sp…
Spatio-Temporal Wind Speed Forecasting using Graph Networks and Novel Transformer Architectures
Lars Ødegaard Bentsen, Narada Dilp Warakagoda, Roy Stenbro +1
This study focuses on multi-step spatio-temporal wind speed forecasting for the Norwegian continental shelf. The study aims to leverage spatial dependencies through the relative ph…