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Review on Design, Optimization and Control of Crude Oil Distillation

Author(s):

Gourav Gagan , Dr.Ambedkar Institute of Technology for Handicapped Kanpur (U.P) 208024; Rajesh Chauhan, Dr.Ambedkar Institute of Technology for Handicapped Kanpur (U.P) 208024; Prashant Kumar, Dr.Ambedkar Institute of Technology for Handicapped Kanpur (U.P) 208024; Subhash Sharma , Dr.Ambedkar Institute of Technology for Handicapped Kanpur (U.P) 208024; Ashutosh Mishra, Dr.Ambedkar Institute of Technology for Handicapped Kanpur (U.P) 208024

Keywords:

Artificial Neural Network; Crude Oil Distillation Column; Genetic Algorithm Framework; Sigmoidal Transfer Function; Back-Propagation Algorithm

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.

Other Details

Paper ID: IJSRDV7I30154
Published in: Volume : 7, Issue : 3
Publication Date: 01/06/2019
Page(s): 1127-1129

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