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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Veröffentlicht in:	Journal of the Taiwan Institute of Chemical Engineers Jg. 146; S. 104779
Hauptverfasser:	Liu, Jialin, Tsai, Bing-Yen, Chen, Ding-Sou
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.05.2023
Schlagworte:	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
Online-Zugang:	Volltext
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