Adaptive control with neural networks-based disturbance observer for a spherical UAV

This paper develops a control scheme for a Spherical Unmanned Aerial Vehicle (UAV) which can be used in complex scenarios where traditional navigation and communications systems would not succeed. The proposed scheme is based on the nonlinear control theory combined with Adaptive Neural-Networks Disturbance Observer (NN-DOB) and controls the attitude and altitude of the UAV in presence of model uncertainties and external disturbances. The NN-DOB can effectively estimate the uncertainties without the knowledge of their bounds and the control system stability is proven using Lyapunov’s stability theorems. Numerical simulation results demonstrate the validity of the proposed method on the UAV under model uncertainties and external disturbances.