13 citations · 18 across the 3 of their papers we have counts for
8 papers
Deep Behaviour Cloning of Model Predictive Control for Real-Time Operation of a Hydrogen-Diesel Dual-Fuel Engine
Alexander Winkler, Neeraj Naduvath Mana, David Gordon +1
Hydrogen-diesel dual-fuel (H2DF) combustion engines offer a promising pathway for decarbonising hard-to-electrify transport sectors, yet their highly nonlinear dynamics and coupled…
Hydrogen-Diesel Dual-Fuel Engine Operation Using Real-Time GRU-Based Nonlinear Model Predictive Control
Alexander Winkler, Vasu Sharma, Julian Bedei +4
Hydrogen-diesel dual-fuel (H2DF) combustion reduces combustion-out CO2 emissions but exhibits nonlinear cycle-to-cycle dynamics at high hydrogen energy shares (HES). This work eval…
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…
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,…
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…
Introducing a Deep Neural Network-based Model Predictive Control Framework for Rapid Controller Implementation
David C. Gordon, Alexander Winkler, Julian Bedei +3
Model Predictive Control (MPC) provides an optimal control solution based on a cost function while allowing for the implementation of process constraints. As a model-based optimal…
Machine Learning Integrated with Model Predictive Control for Imitative Optimal Control of Compression Ignition Engines
Armin Norouzi, Saeid Shahpouri, David Gordon +6
The high thermal efficiency and reliability of the compression-ignition engine makes it the first choice for many applications. For this to continue, a reduction of the pollutant e…
Deep Learning based Model Predictive Control for Compression Ignition Engines
Armin Norouzi, Saeid Shahpouri, David Gordon +6
Machine learning (ML) and a nonlinear model predictive controller (NMPC) are used in this paper to minimize the emissions and fuel consumption of a compression ignition engine. In…