Aircraft Engine MRAC Based on Elman Neural Network

In order to deal with the complexity and variability of the math model of aircraft engine,a self adaptive system of control based on Elman neural network is established.For improving the response results,the DBP of Elman network is adopted simultaneously in NNC and NNI to realize online adjusting and identification of parameters and the convergence of its calculation is testified by Lyapunov Function.The thesis further simulates the control of aircraft turbojet engine of both on-the-ground and in-the-air model with step signal as input,which proves several advantages of this control system such as better adaptive capability,sensitive response and minimal stable error.And theoretic analysis and simulation results are tallied,which prove that the arithmetic and result are correct and effectual,can provide reference for controlling complex dynamic system.