Open AccessResearch Progress of Chemical Process Control and Optimization Based on Neural Network
Author(s) -
Zhihui Zhao,
Xiaofeng Lu
Publication year - 2021
Publication title -
journal of engineering research and reports
Language(s) - English
Resource type - Journals
ISSN - 2582-2926
DOI - 10.9734/jerr/2021/v21i1217506
Subject(s) - artificial neural network , computer science , robustness (evolution) , nervous system network models , artificial intelligence , process (computing) , process control , control engineering , machine learning , time delay neural network , engineering , types of artificial neural networks , biochemistry , chemistry , gene , operating system
Chemical process is usually regarded as a comprehensive system and optimized as a whole because of the interaction and restriction between its operation units. The classical control technology is limited to the control system dealing with single variable. Artificial neural network (ANN) is an algorithmic mathematical model that imitates the behavioral characteristics of animal neural networks for information processing. It has the advantages of nonlinear, large-scale, and strong parallel processing capabilities, as well as robustness. This article summarizes the basic principles and development history of ANN, and analyzes the research progress of chemical process control and optimization based on artificial neural networks in recent years.