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(56v) Inferential Control of Pilot-Plant Distillation Column Using Neural Network Based Soft Sensor

Authors: 
Abdulla, T. A., McKetta Department of Chemical Engineering, The University of Texas at Austin
The development of an inferential soft sensor for pilot-plant distillation column of ethanol-water mixture using neural network (NN) method has been investigated in this work. The lags between the input variables and the output variable vary due to changes in operating conditions. An inferential sensor that can infer the composition of ethanol at the top product using time lags for the input variables and varied first-order time constant lags with the output variable is developed. Based on this soft sensor, an inferential PI controller has been developed. The gain scheduling for this controller has been found necessary to get a good performance.

In summary, a high accuracy soft sensor for the ethanol composition of the top distillation product has been developed and validated. Based on this soft sensor and inferential PI controller, Model Predictive Controller (MPC) for this pilot-plant column will be developed in future work.