Robust Adaptive Nonlinear Control for Tilt-Rotor UAV

This paper deals with a waypoint trajectory following problem for the tilt-rotor UAV under development in Korea (TR-KUAV). In this problem, dynamic model inversion based on the linearized model and Sigma-Phi neural network with adaptive weight update are involved to realize the waypoint following algorithm for the vehicle in the helicopter flight mode (nacelle angle=0 deg). This algorithms consists of two main parts: outer-loop system as a command generator and inner-loop system as stabilizing controller. In this waypoint following problem, the position information in the inertial axis is given to the outer-loop system. From this information, Attitude Command/Attitude Hold logic in the longitudinal channel and Rate Command/Attitude Hold logic in the lateral channel are realized in the inner-loop part of the overall structure of the waypoint following algorithm. The nonlinear simulation based on the TR-KUAV is carried out to evaluate the stability and performance of the algorithm. From the numerical simulation results, the algorithm shows very good tracking performance of passing the waypoints given. Especially, it is observed that ACAH/RCAH logic in the inner-loop has the satisfactory performance due to adaptive neural network in spite of the model error coming from the linear model based inversion.