13 citations · 17 across the 2 of their papers we have counts for
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cs.LG2023★ 4 cited
Transfer of Reinforcement Learning-Based Controllers from Model- to Hardware-in-the-Loop
Mario Picerno, Lucas Koch, Kevin Badalian +4
The process of developing control functions for embedded systems is resource-, time-, and data-intensive, often resulting in sub-optimal cost and solutions approaches. Reinforcemen…
eess.SY2023★ 13 cited
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…