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Contorl-CSTR-using-Reinforcement-learning

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This study explores using RL for CSTR control, assessing effectiveness vs. traditional controllers (PID, MPC). RL learns optimal behavior to maximize rewards, outperforming NMPC with exploration and lower computational load.

Creat2023-09-14T01:35:34
Update2025-03-08T20:47:37
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