Control and Optimization of Chemical Reactors with Model-free Deep Reinforcement Learning
Abstract: Model-based control and optimization is the predominant paradigm in process systems engineering. The performance of model-based methods, however, rely heavily on the accuracy of the process model, which declines over the operation cycle due to various causes, such as catalyst deactivat...
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| Language: | en |
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2020
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| Online Access: | http://hdl.handle.net/10754/664024 |