Control of the speed and exhaust gas temperature in gas turbine using adaptive neuro-fuzzy inference system

Abstract EN

This work proposes the application of the hybrid approach using Adaptive Neuro-Fuzzy Inference System (ANFIS) to control the speed and exhaust gas temperature of a gas turbine.

Create into various parts of the model of the examined gas turbine and given a comprehensive procedure to derive the parameters of the investigated gas turbine using the parameters of Rowen’s model for dynamic studies, the parameters are estimated by use of available operational and performance data.

This paper develops the studied single shaft heavy duty gas turbine model L7001B class 160-MW simple cycle for deriving the parameters of the model.

The obtained results using the Adaptive Neuro- Fuzzy Inference System are validates by several robust tests