Abstract:

In condition of transonic flight, the performance of the angle of attack (AOA) sensor declines remarkably which influences the normal flight seriously. Aiming at the different configurations of AOA sensors when the plane is in flight-test and in equipment and the shortage of tranditional back-propagation (BP) algorithm, an algorithm based on improved BP algorithm (Levenberg Marquardt algorithm, LM algorithm) is designed to compensate and correct the transonic AOA. The BP neural network based on LM algorithm has been trained and tested with actual flight data. The results show that the AOA, which is corrected by the BP neural network as compensation, could basically eliminate the violent fluctuations of the measured AOA in transonic phase. And its tendency coincides with the true AOA with a small error.