Deep reinforcement learning based controller with dynamic feature extraction for an industrial claus process

•The DRL-based controller integrating with the process dynamics is developed.•The dynamic feature is extracted from the historical data using the Seq2seq network.•The controller was trained by interacting with the Seq2seq model.•The standard deviation of the control variable in the industrial Claus...

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Vydané v:	Journal of the Taiwan Institute of Chemical Engineers Ročník 146; s. 104779
Hlavní autori:	Liu, Jialin, Tsai, Bing-Yen, Chen, Ding-Sou
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 01.05.2023
Predmet:	Actor-critic networks Deep reinforcement learning industrial Claus process Sequence-to-sequence network Twin delayed deep deterministic policy gradient algorithm Deep reinforcement learning industrial Claus process Actor-critic networks Sequence-to-sequence network Twin delayed deep deterministic policy gradient algorithm
ISSN:	1876-1070, 1876-1089
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