Selective Control of a Gas-Turbine Engine

• Published in: Russian electrical engineering 2020-11, Vol.91 (11), p.665-668
• Main Authors: Khizhnyakov, Yu. N., Yuzhakov, A. A., Storozhev, S. A., Nikulin, V. S.
• Format: Article
• Language: English
• Subjects: Aircraft engines; Artificial neural networks; Automatic control; Centroids; Combustion chambers; Combustion products; Electric power generation; Engineering; Fuzzy control; Fuzzy logic; Fuzzy sets; Fuzzy systems; Gas turbine engines; Gas-fired power plants; Genetic algorithms; Linear functions; Machines; Manufacturing; Multiagent systems; Neural networks; Nonlinear control; Parameters; Processes; Rotation; Rotors; Soft computing; Superchargers; Toolkits; Turbines
• ISSN: 1068-3712; 1934-8010
• DOI: 10.3103/S1068371220110073

The toolkit of soft computing is based on fuzzy systems, fuzzy neural network models, genetic algorithms, etc., with their strengths and weaknesses. This article analyzes the application of this toolkit to aviation gas-turbine engines (GTEs) used in aircraft and gas-turbine power plants. In the theory of automatic control their GTEs are nonlinear objects without any mathematical description but with one input and several outputs. In the course of running a GTE, it is necessary to continuously control its parameters, such as the combustion chamber temperature, the rotation frequency of the rotor of the fan’s free turbine, and the turbocharger rotor frequency. The GTE is supplied with fuel through a selective regulator that analyzes deviations in the parameters of all of the loops in an asynchronous and logically continuous manner. The multiagent or selector-free control of the GTE is based on designing a fuzzy state controller using linear functions of membership for all of the input parameters in a range from 0 to 1. The interparameter connections are established by fuzzy implication with the help of layers the number of which is equal to the number of terms in a specific term set. The fuzzy composition is made up graphically by the pointwise summation of ordinates of truncated figures according to Mamdani. Defuzzification is performed by the centroid technique, including an even partition along the X -axis of the resulting figure. The fuel consumption of the dispenser allows finding the fan rotation frequency, the turbocharger rotation frequency, and the temperature of the combustion products behind the combustion chamber within specified limits.