Development of the automatic supervisory control system based on fuzzy inference

The development of the supervisory control system designed to ensure the automatic stabilization of the petroleum processing parameters in a multi-flow furnace is considered. The structure of the subsystem that generates the setpoints of the local flow controllers in order to optimize technological...

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Published inJournal of physics. Conference series Vol. 1260; no. 3; pp. 32010 - 32018
Main Authors Denisova, L A, Alekseytsev, D M, Meshcheryakov, V A
Format Journal Article
LanguageEnglish
Published Bristol IOP Publishing 01.08.2019
Subjects
Automatic control
Control systems design
Controllers
Fuzzy control
Genetic algorithms
Inference
Local flow
Physics
Process parameters
Subsystems
Supervisory control
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Summary:The development of the supervisory control system designed to ensure the automatic stabilization of the petroleum processing parameters in a multi-flow furnace is considered. The structure of the subsystem that generates the setpoints of the local flow controllers in order to optimize technological processes is proposed. The supervisory subsystem is designed to minimize two criteria of the controlled values. The genetic algorithm is used to tune the parameters of the fuzzy inference based supervisory subsystem. The description of the system implementation based on intelligent controllers is suggested as well as the results of system simulation in MATLAB.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/1260/3/032010