On-board Real-time Adaptive Modeling And High Stability Control Technology Of Aero-engine

Aero-engine's on-board real-time adaptive modeling and high stability control technology during super dynamic flight are mainly included in present thesis.Based on Kalman filter(KF) method and support vector machine method, engine on-board adaptive models are established respectively. Firstly, an adaptive model which based on an improved Kalman filter is developed, in which the output error feedback is added to correct the Kalman filter's output parameters in real time; another improved Kalman filter is also designed, which is used on engine adaptive model. In view of the conflict between more engine health parameters and less sensor number, an embedded adaptive engine model based on an SVD-Kalman filter is designed, to solve the problem of adaptive model based on smaller sensors. In addition, with the help of artificial intelligence technology, R-Reduction Least Squares Support Vector Regression Machine(RR-LSSVRM) method is used to design an adaptive model , which is validated in a narrow flight envelop.A study of engine stability control for super-maneuvering flight is carried out. an advanced predictive engine control system using angle of attack (AOA) predictive-based model is designed: in order to estimate the inlet engine-face distortion in real time, an AOA predictive model is established firstly; based on the model, high stability predictive controller is designed using augmented LQR(ALQR) method. Finally, a digital simulation is performed in the engine / three degree-of-freedom aircraft nonlinear integrated model platform.