Application of Artificial Neural Network in Distillation System: A Critical Review of Recent Progress
Chunli Li
School of Chemical Engineering and Technology, Hebei University of Technology, Tianjin 300130, China
Chunyu Wang *
School of Chemical Engineering, East China University of Science and Technology, Shanghai 200237, China
*Author to whom correspondence should be addressed.
Abstract
Distillation is a unit operation with multiple input parameters and multiple output parameters. It is characterized by multiple variables, coupling between input parameters, and non-linear relationship with output parameters. Therefore, it is very difficult to use traditional methods to control and optimize the distillation column. Artificial Neural Network (ANN) uses the interconnection between a large number of neurons to establish the functional relationship between input and output, thereby achieving the approximation of any non-linear mapping. ANN is used for the control and optimization of distillation tower, with short response time, good dynamic performance, strong robustness, and strong ability to adapt to changes in the control environment. This article will mainly introduce the research progress of ANN and its application in the modeling, control and optimization of distillation towers.
Keywords: Artificial neural network, distillation, BPNN, RBFNN