DME production by methanol dehydration using reactive distillation has a lot of potentials. However, the DME purity and methanol conversion is hard to be controlled and need inferential variable to be controlled. Data driven soft sensors can be utilised to select inferential variables, which can be used to control DME production by using reactive distillation. The data was collected from process simulation using ASPEN and analyzed by using PCA (Principal Component Analysis) and PLSR (Partial Least Squares Regression). The results show that based on the data driven soft sensors method, the DME purity can be controlled by using T4 as an inferential variable and ratio reflux as the manipulated variable. However, the methanol conversion is hard to be controlled because the potential inferential temperature was not significantly affected by reflux ratio and reboiler duty as the candidate manipulated variables.
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