Large-scale multi-agent reinforcement learning-based method for coordinated output voltage control of solid oxide fuel cell
Author:
Funder
South China University of Technology
National Natural Science Foundation of China
Publisher
Elsevier BV
Subject
Fluid Flow and Transfer Processes,Engineering (miscellaneous)
Reference33 articles.
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1. Adaptive data-driven controller based on fractional calculus for solid oxide fuel cell;International Journal of Dynamics and Control;2024-06-17
2. Recent progress and challenges of multi-stack fuel cell systems: Fault detection and reconfiguration, energy management strategies, and applications;Energy Conversion and Management;2023-06
3. Optimal dual-model controller of solid oxide fuel cell output voltage using imitation distributed deep reinforcement learning;International Journal of Hydrogen Energy;2023-04
4. Multi‐agent reinforcement learning for process control: Exploring the intersection between fields of reinforcement learning, control theory, and game theory;The Canadian Journal of Chemical Engineering;2023-03-02
5. Optical Character Recognition of Power Equipment Nameplate for Energy Systems Based on Recurrent Neural Network;Frontiers in Energy Research;2022-08-10
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