Neural network algorithm and its application in reactive distillation
This is an incremental review for the chemical engineering industry, focusing on using neural networks to handle nonlinearities in reactive distillation.
The paper addresses the challenge of controlling and optimizing reactive distillation processes, which exhibit highly nonlinear robust behavior, by summarizing the application of neural network algorithms to provide a reference for industry technology development.
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.