Learning Control of Tandem-Wing Tilt-Rotor UAV with Unsteady Aerodynamic Model

摘要

This paper presents a novel transition flight mathematical model of tilt-rotor unmanned aerial vehicles and demonstrates an application of a novel learning controller on the developed model. Instead of conventional steady aerodynamic models, an unsteady aerodynamic model capable of representing rapid changes in the air flow is developed for the tilt-rotor transition flight. The vehicle is controlled by a neuro-fuzzy learning controller, consisting of a type-2 fuzzy neural network and a proportional-derivative controller. Its results are compared with the results of proportional-integral-derivative controllers. It is evident from the results that the learning controller is capable of capturing the rapid changes in the aerodynamics and outperforms its nonlearning counterpart under perturbed conditions.