8 papers
Robust Scenario-Based Data-Enabled Predictive Control of a Battery Energy Storage System: An Experimental Study
Sebastian Zieglmeier, Nikolas Recke, Mathias Hudoba de Badyn
Battery energy storage systems must respect strict state-of-charge (SOC) limits to prevent overcharge and deep discharge, a task complicated by measurement noise and costly-to-mode…
Model-Free Control for Residential Heating: Deployment and Simulation of Nonlinear Data-Enabled Predictive Control
Sebastian Zieglmeier, Chris Verhoek, Jaap Eising +1
Residential heating accounts for a large share of building energy use, and predictive control strategies can reduce it by anticipating rather than reacting to the room temperature…
Data-driven predictive control of nonlinear systems using weighted regularization
Fritz A. Engeln, Sebastian Zieglmeier, Marta Zagórowska +1
Data-driven control methods, like Data-enabled Predictive Control (DeePC), are often formulated for linear systems, where the principle of superposition allows global system behavi…
Scenario-based Data-Enabled Predictive Control: Robustification via the Scenario Approach
Sebastian Zieglmeier, Nikolas Recke, Mathias Hudoba de Badyn
This paper proposes Scenario-Based Data-Enabled Predictive Control (Scenario-DeePC), which integrates the scenario optimization framework into Data-enabled Predictive Control (DeeP…
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…
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…