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

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...

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Bibliographic Details

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
ISSN:	0967-0661, 1873-6939
Online Access:	Get full text
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