FINITE TIME TRAJECTORY TRACKING CONTROL OF A QUADROTOR BASED ON ARTIFICIAL NEURAL NETWORK

Abstract

In this paper, a robust hierarchical method for trajectory tracking control of a quadrotor unmanned aerial vehicle (UAV) subjected to parameter uncertainties and external disturbances is presented. A robust control scheme based on a fast nonsingular terminal sliding mode strategy is designed to achieve fast response and excellent tracking accuracy. Moreover, a radial basis function artificial neural network with online adaptive schemes to estimate unknown aerodynamic parameters and external disturbances is developed to improve the control performance and reduce the chattering phenomenon. Numerical simulation and experimental results are used to validate the effectiveness of the proposed control method.