Deep reinforcement learning with shallow controllers: An experimental application to PID tuning

• Published in: Control engineering practice Vol. 121; p. 105046
• Main Authors: Lawrence, Nathan P., Forbes, Michael G., Loewen, Philip D., McClement, Daniel G., Backström, Johan U., Gopaluni, R. Bhushan
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.04.2022
• Subjects: Deep learning; PID control; Process control; Process systems engineering; Reinforcement learning; Deep learning; PID control; Process systems engineering; Process control; Reinforcement learning

Deep reinforcement learning (RL) is an optimization-driven framework for producing control strategies for general dynamical systems without explicit reliance on process models. Good results have been reported in simulation. Here we demonstrate the challenges in implementing a state of the art deep R...