Development of genetic programming based softsensor model for styrene polymerization process and its application in model based control
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- @InProceedings{Ghugare:2016:ICC,
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author = "Suhas B. Ghugare and Sanjeev S. Tambe",
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booktitle = "2016 Indian Control Conference (ICC)",
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title = "Development of genetic programming based softsensor
model for styrene polymerization process and its
application in model based control",
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year = "2016",
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pages = "238--244",
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abstract = "In recent years, soft sensors have been established as
a valuable alternative to the traditional hardware
sensors for the acquisition of critical information
regarding difficult-to-measure process variables and/or
parameters in chemical process monitoring and control.
Soft-sensors can also be modified as a novel process
identification tool for process monitoring and model
based control. Often, in polymer industries the main
polymerization reaction is highly nonlinear and complex
to model accurately by the conventional first
principle's approach. In such cases, genetic
programming (GP) - a novel artificial
intelligence-based exclusively data-driven modelling
technique - can be employed for process identification.
In this work GP-based soft sensors have been developed
for a continuous styrene polymerization reactor. The
resulting GP-based models (soft sensor) showed high
prediction and generalisation performances. The best
performing model was successfully used in designing a
model predictive control (MPC) scheme for the
polymerization reactor.",
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keywords = "genetic algorithms, genetic programming",
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DOI = "doi:10.1109/INDIANCC.2016.7441134",
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month = jan,
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notes = "Also known as \cite{7441134}",
- }
Genetic Programming entries for
Suhas B Ghugare
Sanjeev S Tambe
Citations