Application of Neural Network Algorithm in Optimal Control of Ethylene Distillation Tower
Asian Journal of Research in Computer Science · pp. 19–29 · Published 28 May 2021
10.9734/ajrcos/2021/v9i230217Abstract
For some nonlinear dynamic systems with uncertainties or disturbances, neural networks can perform intelligent cognition and simulation on them, achieve a good system description, and further realize intelligent control. Aiming at the ethylene rectification process, in order to avoid the time delay of complex rectification process modeling and large-scale process simulation software interface program, and to improve the simulation operation speed, the optimization model combined with the learning function of the neural network is used for the simulation calculation of the rectification process. It can meet the time and accuracy requirements of online optimization. This article outlines several commonly used neural network algorithms and their related applications in ethylene distillation, aiming to provide reference for the development and innovation of industry technology.
Cited by 1
Chunyu Wang, Lujie Wang · Journal of Engineering Research and Reports · 2023
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