Pitch angle control of fixed wing airplane autopilot using artificial neural networks based model reference adaptive control

Abstract

This thesis investigates the advantages of an adaptive control based on the artificial neural network for the control of pitch angle of fixed-wing airplane autopilot systems. Flight control of a fixed-wing airplane is not suitable to work on due to unstable and time-varying conditions. Therefore, Lyapunov’s stability analysis in a direct model reference based on artificial neural networks strategy has been applied, for the control of a fixed-wing airplane. The autopilot is one of the vital parts of flying airplanes which establishes stability and accomplishment of the desired flight control