Abstract
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.
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