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For the aerial manipulator that performs aerial work tasks, the actualoperating environment it faces is very complex, and it is affected by internaland external multi-source disturbances. In this paper, to effectively improvethe anti-disturbance control performance of the aerial manipulator, an adaptiveneural network backstepping control method based on variable inertia parametermodeling is proposed. Firstly, for the intense internal coupling disturbance,we analyze and model it from the perspective of the generation mechanism of thecoupling disturbance, and derive the dynamics model of the aerial manipulatorsystem and the coupling disturbance model based on the variable inertiaparameters. Through the proposed coupling disturbance model, we can compensatethe strong coupling disturbance in a way of feedforward. Then, the adaptiveneural network is proposed and applid to estimate and compensate the additionaldisturbances, and the closed-loop controller is designed based on thebackstepping control method. Finally, we verify the correctness of the proposedcoupling disturbance model through physical experiment under a large rangemotion of the manipulator. Two sets of comparative simulation results alsoprove the accurate estimation of the proposed adaptive neural network foradditional disturbances and the effectiveness and superiority of the proposedcontrol method.

Adaptive Neural Network Backstepping Control Method for Aerial Manipulator Based on Variable Inertia Parameter Modeling