IT2-Neuro-Fuzzy Wavelet Network with Jordan Feedback Structure for the Control of Aerial Robotic Vehicles with External Disturbances

Taking into account the various challenges due to uncertainties and disturbances while operating with aerial robotic vehicles (ARVs) in a harsh and extreme environment, a novel adaptive control scheme named Interval-Type-2 Neuro-Fuzzy Wavelet (IT2-NFW) network with Jordan feedback structure has been proposed in this work. The ARVs considered in this study are under the influence of external disturbances due to which the ARV system becomes uncertain and hence becomes very difficult to control. The suggested control strategy can manage system uncertainty more efficiently. With high computational capacity, little computational load, and a quick convergence rate, the proposed IT2-NFW control method can accurately simulate system uncertainties and track the reference trajectory. The controller’s stability has been demonstrated by means of Lyapunov’s method, and the controller’s assured convergence has been demonstrated. Finally, the controller’s effectiveness and efficiency have been demonstrated by controlling an aerial robotic vehicle.