Modelling and comparison of compressor performance parameters by using ANFIS

Abstract

Developing a robust control algorithm for an aircraft engine requires an accurate nonlinear mathematical model. In formation of a nonlinear mathematical model, some components like compressor and turbine are modeled by using component maps. These maps show the connection between the compressor performance parameters. To show this connection, map data is digitized by using some techniques. In this study, we digitized a compressor map data by using ANFIS (Adaptive Neuro Fuzzy Inference System). RMSE (Root Mean Square Error) were calculated for different types of FIS (Fuzzy Inference System) structures constructed with different number of membership functions. The model was formed by using all valid data which is collected from a small turboprop engine compressor. Results demonstrate that the designed ANFIS structure can serve as an alternative model to estimate both online and offline compressor performance parameters