TITLE:
A Review of an Expert System Design for Crude Oil Distillation Column Using the Neural Networks Model and Process Optimization and Control Using Genetic Algorithm Framework
AUTHORS:
Lekan Taofeek Popoola, Gutti Babagana, Alfred Akpoveta Susu
KEYWORDS:
Artificial Neural Network; Crude Oil Distillation Column; Genetic Algorithm Framework; Sigmoidal Transfer Function; Back-Propagation Algorithm
JOURNAL NAME:
Advances in Chemical Engineering and Science,
Vol.3 No.2,
April
29,
2013
ABSTRACT: This paper presents a comprehensive review
of various traditional systems of crude oil distillation column design, modeling,
simulation, optimization and control methods. Artificial neural network (ANN), fuzzy
logic (FL) and genetic algorithm (GA) framework were chosen as the best
methodologies for design, optimization and control of crude oil distillation
column. It was discovered that many past researchers used rigorous simulations which
led to convergence problems that were time consuming.
The use of dynamic mathematical models was also challenging as these models were also
time dependent. The proposed methodologies use back-propagation algorithm to replace
the convergence problem using error minimal method.