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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Veröffentlicht in:	Control engineering practice Jg. 121; S. 105046
Hauptverfasser:	Lawrence, Nathan P., Forbes, Michael G., Loewen, Philip D., McClement, Daniel G., Backström, Johan U., Gopaluni, R. Bhushan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.04.2022
Schlagworte:	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-Zugang:	Volltext
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