DocumentCode
3427695
Title
Fuzzy supervisory controller tuning and analysis for optimal steam distribution in industry
Author
Bratina, Bozidar ; Muskinja, Nenad
Author_Institution
Fac. of Electr. Eng. & Comput. Sci., Univ. of Maribor, Maribor, Slovenia
fYear
2013
fDate
1-4 July 2013
Firstpage
1512
Lastpage
1518
Abstract
Distribution of high-pressure steam in industry must be adequately synchronised to production cycles and their dynamic consumption demands. In many cases high-pressure steam plants have also steam turbine installation, which demands stable input/output operating conditions to produce and maintain nominal electrical energy production. The paper presents an offline concept of Fuzzy supervisory control scheme development, tuning and implementation, in order to avoid unnecessary interference of production cycles. Fuzzy rule database is developed upon process measurements and verified by data-driven process model (auto-associative neural network), and implemented into PLC (commercial platform that supports Fuzzy implementation). Initial set up of Fuzzy input/output scaling factors (gains) is defined by cooperative global optimization algorithm, to avoid implementation issues. The use of Fuzzy supervisory controller resulted in more stable and increased production of electrical energy, where efficiency of the steam turbine output has been raised for approximately 5%.
Keywords
SCADA systems; fuzzy control; neurocontrollers; optimisation; programmable controllers; steam power stations; steam turbines; PLC; autoassociative neural network; cooperative global optimization algorithm; data-driven process model; fuzzy input-output scaling factors; fuzzy rule database; fuzzy supervisory controller tuning; optimal steam distribution; steam plants; steam turbine installation; Neurons; Optimization; Process control; Supervisory control; Turbines; Valves; control; fuzzy control; modeling; neural networks; optimization; steam turbine;
fLanguage
English
Publisher
ieee
Conference_Titel
EUROCON, 2013 IEEE
Conference_Location
Zagreb
Print_ISBN
978-1-4673-2230-0
Type
conf
DOI
10.1109/EUROCON.2013.6625178
Filename
6625178
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