4 papers
Safe Reinforcement Learning for Real-World Engine Control
Julian Bedei, Lucas Koch, Kevin Badalian +3
This work introduces a toolchain for applying Reinforcement Learning (RL), specifically the Deep Deterministic Policy Gradient (DDPG) algorithm, in safety-critical real-world envir…
Incorporating a Deep Neural Network into Moving Horizon Estimation for Embedded Thermal Torque Derating of an Electric Machine
Alexander Winkler, Pranav Shah, Katrin Baumgärtner +3
This study presents a novel state estimation approach integrating Deep Neural Networks (DNNs) into Moving Horizon Estimation (MHE). This is a shift from using traditional physics-b…
Hybrid Reinforcement Learning and Model Predictive Control for Adaptive Control of Hydrogen-Diesel Dual-Fuel Combustion
Julian Bedei, Murray McBain, Alexander Winkler +3
Reinforcement Learning (RL) and Machine Learning Integrated Model Predictive Control (ML-MPC) are promising approaches for optimizing hydrogen-diesel dual-fuel engine control, as t…
Safe Reinforcement Learning-based Control for Hydrogen Diesel Dual-Fuel Engines
Vasu Sharma, Alexander Winkler, Armin Norouzi +3
The urgent energy transition requirements towards a sustainable future stretch across various industries and are a significant challenge facing humanity. Hydrogen promises a clean,…