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Electrical Engineering and Systems Science > Systems and Control

arXiv:2110.09021 (eess)
[Submitted on 18 Oct 2021]

Title:Artificial Neural Network and Its Application Research Progress in Chemical Process

Authors:Li Sun, Fei Liang, Wutai Cui
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Abstract:Most chemical processes, such as distillation, absorption, extraction, and catalytic reactions, are extremely complex processes that are affected by multiple factors. The relationships between their input variables and output variables are non-linear, and it is difficult to optimize or control them using traditional methods. Artificial neural network (ANN) is a systematic structure composed of multiple neuron models. Its main function is to simulate multiple basic functions of the nervous system of living organisms. ANN can achieve nonlinear control without relying on mathematical models, and is especially suitable for more complex control objects. This article will introduce the basic principles and development history of artificial neural networks, and review its application research progress in chemical process control, fault diagnosis, and process optimization.
Subjects: Systems and Control (eess.SY)
Cite as: arXiv:2110.09021 [eess.SY]
  (or arXiv:2110.09021v1 [eess.SY] for this version)
  https://doi.org/10.48550/arXiv.2110.09021

Submission history

From: Fei Liang [view email]
[v1] Mon, 18 Oct 2021 05:35:46 UTC (284 KB)
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