Fuzzy Control of Combustion with Genetic Learning Automata
| Authors: | Himer Zoltán, Oulu University, Finland
Dévényi Géza, Technical University of Budapest, Hungary
Kovács Jenő, Oulu University, Finland
Kortela Urpo, Oulu University, Finland |
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| Topic: | 6.3 Power Plants and Power Systems |
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| Session: | Thermal Power Plant Control |
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| Keywords: | Combustion control, non-linear systems, ANFIS, Combustion control, Genetic Learning Automata |
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Abstract
This paper demonstrates the application of ANFIS a nonlinear Multi Input Single Output fuel feeding and combustion system and a fuzzy controller design for the system with optimization with Genetic Learning Automata (GLA).An ANFIS model has been developed to determine the exact amount of fuel fed to a combustion chamber. This property is impossible to measure directly, but it is required for improving combustion control. The control of the combustion base on two Takagi-Sugeno type controllers, which were optimized by GLA. The control system has been validated on experiment data obtained in a case-study power plant. The results have shown that the system is able to capture the nonlinear feature of the fuel feeding system.
