Abstract
Improving the efficiency of the gas transportation industry is a relevant task. In this work, the gas transmission system is considered as a control object. The graph of a model describing a gas balance control system is constructed. A method for synthesis of a control algorithm is determined. Topological, structural and parametric synthesis problems are solved. This article discusses the possibility of using a control method based on a discrete automaton and machine learning methods, in particular, LSTM neural networks. Sets of their input parameters and hyper parameters are determined; imbalance causes are classified based on a criticality matrix. A model of the gas transmission system was built in the MatLab environment.
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