Neural network algorithm and its application in reactive distillation

TL;DR

This paper reviews how neural network algorithms are applied to reactive distillation, a process combining chemical reactions and separation, to improve control and optimization due to its nonlinear behavior.

Contribution

It summarizes the characteristics and recent research progress of neural network applications in reactive distillation technology.

Findings

Neural networks effectively model nonlinear behaviors in reactive distillation.

Application of neural networks improves process control and optimization.

The paper provides a reference for industrial technological development.

Abstract

Reactive distillation is a special distillation technology based on the coupling of chemical reaction and distillation. It has the characteristics of low energy consumption and high separation efficiency. However, because the combination of reaction and separation produces highly nonlinear robust behavior, the control and optimization of the reactive distillation process cannot use conventional methods, but must rely on neural network algorithms. This paper briefly describes the characteristics and research progress of reactive distillation technology and neural network algorithms, and summarizes the application of neural network algorithms in reactive distillation, aiming to provide reference for the development and innovation of industry technology.