The proposed method is applied to a simulated fed-batch process and it gives better optimization control performance than other control strategies. Published in ...
Section II introduces the traditional reinforcement learning algorithm and the improved Q-learning. The models of a fed-batch process are given in Section III.
The proposed stochastic multi-step action Q-learning algorithm (SMSA) is applied to a simulated fed-batch process and it gives better optimization control ...
B ATCH processes, as an important chemical process, are expected to generate higher value products, such as desirable chemicals, polymers and ...
Neural networks and traditional reinforcement learning have been applied to control and optimize batch processes. However, they usually lack robustness and ...
This paper examines the advantages that RL offers over the traditional model-based optimal control methods and how it can be tailored to better address the ...
Then, we proposed two improved reinforcement learning algorithms to control the different batch processes, respectively. Finally, the control results of ...
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Jun 15, 2024 · Highlights · A novel deep reinforcement learning (DRL)-based control framework for the industrial scale fed-batch penicillin production.
Optimization control of a fed-batch process using an improved reinforcement learning algorithm. P Zhang, J Zhang, B Hu, Y Long. 2019 IEEE Conference on ...
... optimization (TRPO) algorithms for learning control policies. We first develop a policy update scheme with guaranteed monotonic improvement, and then we ...