Adaptive Control Using Neural Network for Command Following of Tilt-Rotor Airplane in 0$^{\it 0}$ -Tilt Angle Mode

Abstract

This paper deals with an autonomous flight algorithm design problem for the tilt-rotor airplane under development by Korea Aerospace Research Institute for simulation study. The objective of this paper is to design a guidance and control algorithm to follow the given command precisely. The approach to this objective is that model-based inversion is applied to the highly nonlinear tilt-rotor dynamics at fixed-wing mode (nacelle angle=0 deg), and then the classical controller is designed to satisfy overall system stabilization and precise command following performance. Especially, model uncertainties due to the tilt-rotor model itself and inversion process are adaptively compensated for in a simple neural network for performance robustness. The designed algorithm is evaluated from the nonlinear airplane simulation in fixed-wing mode to analyze the command following performance for given trajectory. The simulation results show that the command following performance is satisfactory and control responses are within control limits without saturation.