Real-Time Optimization and Control of Nonlinear Processes Using Machine Learning
Machine learning has attracted extensive interest in the process engineering field, due to the capability of modeling complex nonlinear process behavior. This work presents a method for combining neural network models with first-principles models in real-time optimization (RTO) and model predictive...
Main Authors: | Zhihao Zhang, Zhe Wu, David Rincon, Panagiotis D. Christofides |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2019-09-01
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Series: | Mathematics |
Subjects: | |
Online Access: | https://www.mdpi.com/2227-7390/7/10/890 |
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