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首页> 外文期刊>Advances in Chemical Engineering and Science >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
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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

机译：基于神经网络模型的原油蒸馏塔专家系统设计与遗传算法框架的优化控制研究综述

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摘要

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.
机译：本文对各种传统的原油蒸馏塔系统的设计，建模，仿真，优化和控制方法进行了全面的回顾。人工神经网络（ANN），模糊逻辑（FL）和遗传算法（GA）框架被选为原油蒸馏塔设计，优化和控制的最佳方法。结果发现，许多过去的研究人员都使用了严格的模拟，这导致了收敛问题，这非常耗时。动态数学模型的使用也具有挑战性，因为这些模型还与时间有关。所提出的方法使用反向传播算法来替换误差最小方法的收敛问题。

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