Thrust performance modelling and optimization for aircraft fadec system

Within the scope of this thesis; engine performance models have been developed for different RPM values of a turboprop engine used in the aviation and defense industry. The models in question were modeled with 2 different population-based metaheuristic algorithms as single input single output (SISO) and multiple input single output (MISO) systems. In the model, the Genetic Algorithm, which is accepted as a good modeling algorithm in many areas in continuous systems in the literature, and the Artificial Bee Colony Algorithm, which is relatively less applied in this field and has a wider research area in aviation models, are used. The output of the system is determined as Torque (N.m) and the input values are RPM and air flow. The validity and reliability of the model is defined by multiple error indexes that are commonly used in literature by comparing the outcomes with test-cell experiment results. The efficiencies of the algorithms are compared to each other by using computational indexes such as max. number of iterations, and CPU processing time. Finally, the results obtained were applied to the Full Authority Digital Engine Control (FADEC) system.