Intelligent control for the main fuel flow of the F-100 turbofan engine

A fuzzy logic controller is proposed in this paper for the main fuel flow of the F-100 turbofan engine. The fuzzy logic controller is designed in a way that the turbo engine will respond to the input signal at a minimum time without violating any safety limits, including thermodynamic, mechanical, and structural limits. Design of such a fuzzy logic controller by trial-and-error method is time-consuming. To avoid this problem, the genetic algorithm is applied for off-line learning the most suitable design parameters of the fuzzy logic controller. Finally, for full flight-envelope operation, the same design procedure is applied to design a fuzzy logic controller at 14 selected design operating points within the operating envelope. A feedforward error-back-propagation neural network is then used to learn the mapping of engine's altitude and Mach number into the parameters of the fuzzy logic controller.