Robust adaptive neural network trajectory tracking control design for the quadrotor UAV elastic suspension system

For the problems of difficult position control and load swing reduction caused by external disturbances in the system of quadrotor UAV with suspended load, the approximation ability of radial basis function neural network (RBFNN) algorithm to the unknown function is used to compensate the external disturbances. A new robust adaptive neural network (RANN) trajectory tracking control scheme is designed. The stability of closed-loop system is analyzed through Lyapunov stability theory. Finally, the performance of the proposed control scheme is verified via numerical simulations.