Lancaster EPrints

Using Evolving Fuzzy Models to predict Crude Oil Distillation Side Streams

Macias-Hernandez, Jose J. and Angelov, Plamen and Zhou, Xiaowei (2011) Using Evolving Fuzzy Models to predict Crude Oil Distillation Side Streams. In: Computer-Aided Design, Manufacturing, Modeling and Simulation :. Trans-Tech Publications, Zurich, pp. 432-437. ISBN 978-3-03785-236-1

Full text not available from this repository.


Prediction of the properties of the crude oil distillation side streams based on statistical methods and laboratory-based analysis has been around for decades. However, it is difficult to identify, control or compensate the dynamic process behavior and the errors from instrumentation for an online model prediction. The objective of this work is to report an application and a study of a novel technique for real-time modelling, namely eXtended Evolving Fuzzy Takagi-Sugeno models (xTS) for prediction and online monitoring of these properties of the refinery distillation process. The results include the online prediction of Soft Sensors for distillation of Naptha and Gasoil Side Streams. The application predicts the quality of the side stream evolving its fuzzy structure and cluster parameters.

Item Type: Contribution in Book/Report/Proceedings
Subjects: ?? qa75 ??
Departments: Faculty of Science and Technology > School of Computing & Communications
ID Code: 58698
Deposited By: ep_importer_pure
Deposited On: 01 Oct 2012 09:27
Refereed?: No
Published?: Published
Last Modified: 01 Aug 2018 14:46
Identification Number:

Actions (login required)

View Item