Optimal dual-model controller of solid oxide fuel cell output voltage using imitation distributed deep reinforcement learning

Solid oxide fuel cell (SOFC) is disadvantaged by significant nonlinearity, which makes it difficult to control output voltage of SOFC and satisfy the constraints of fuel utilization simultaneously. In order to solve this problem, a dual-model control framework (DMCF) is proposed. In particular, ther...

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Vydané v:	International journal of hydrogen energy Ročník 48; číslo 37; s. 14053 - 14067
Hlavní autori:	Li, Jiawen, Cui, Haoyang, Jiang, Wei, Yu, Hengwen
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 30.04.2023
Predmet:	Deep reinforcement learning Fuel utilization Imitation distributed deep deterministic policy gradient algorithm (ID3PG) Optimal control framework Output voltage control Solid oxide fuel cell Deep reinforcement learning Optimal control framework Solid oxide fuel cell Output voltage control Fuel utilization Imitation distributed deep deterministic policy gradient algorithm (ID3PG)
ISSN:	0360-3199, 1879-3487
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