Adaptive neural network-based robust <i>H</i><SUB align="right">∞ tracking control of a quadrotor UAV under wind disturbances

The paper deals with the stabilisation and trajectory tracking control of an autonomous quadrotor helicopter system in presence wind disturbances. proposed adaptive controller uses radial basis function neural networks (RBF NNs) to approximate unknown nonlinear functions system. Two controllers are this handle modelling errors external disturbances: H∞ H∞-ANC H∞-based sliding mode H∞-ANSMC. design approach combines robustness (SMC) ability deal parameter uncertainties bounded Furthermore, RBF models derived using Lyapunov stability analysis. simulation results show that H∞-ANSMC is able eliminate chattering phenomenon, reject perturbation mismatch leads a better performance than H∞-ANC. A comparative study between presented discussed.