Robust predictive control of a gasoline debutanizer column

Model Predictive Inferential Control of a Distillation Column

Typical production objectives in distillation process require the delivery of products whose compositions meet certain specifications. The distillation control system, therefore, must hold product compositions as near the set points as possible in faces of upset. In this project, inferential model predictive control, that utilizes an artificial neural network estimator and model predictive cont...

robust control of a high-purity disttilation column using synthesis

Composition Prediction of a Debutanizer Column

Debutanizer column is an important unit operation in petroleum refining industries. The design of online composition prediction by using neural network will help improve product quality monitoring in an oil refinery industry by predicting the top and bottom composition of n-butane simultaneously and accurately for the column. The single dynamic neural network model can be used and designed to o...

Multivariable control of a debutanizer column using equation based artificial neural network model inverse control strategies

The debutanizer column is an important unit operation in petroleum refining industries as it is the main column to produce liquefied petroleum gas as its top product and light naphtha as its bottom product. This system is difficult to handle from a control standpoint due to its nonlinear behavior, multivariable interaction and existence of numerous constraints on both its manipulated and state ...

Neural-based Monitoring of a Debutanizer Distillation Column

In this paper a neural approach to distillation columns modelling is described. In particular a Debutanizer colums is considered and a real-time estimate of the butane percentage (C4) in the bottom draw (C5) is obtained by a NARMAX model implemented with a Multi-Layer Perceptron. The analyser of the C4 in C5 percentage used at present, provides a measure after a great and unknown delay, and is ...