  For the aerial manipulator that performs aerial work tasks, the actual
operating environment it faces is very complex, and it is affected by internal
and external multi-source disturbances. In this paper, to effectively improve
the anti-disturbance control performance of the aerial manipulator, an adaptive
neural network backstepping control method based on variable inertia parameter
modeling is proposed. Firstly, for the intense internal coupling disturbance,
we analyze and model it from the perspective of the generation mechanism of the
coupling disturbance, and derive the dynamics model of the aerial manipulator
system and the coupling disturbance model based on the variable inertia
parameters. Through the proposed coupling disturbance model, we can compensate
the strong coupling disturbance in a way of feedforward. Then, the adaptive
neural network is proposed and applid to estimate and compensate the additional
disturbances, and the closed-loop controller is designed based on the
backstepping control method. Finally, we verify the correctness of the proposed
coupling disturbance model through physical experiment under a large range
motion of the manipulator. Two sets of comparative simulation results also
prove the accurate estimation of the proposed adaptive neural network for
additional disturbances and the effectiveness and superiority of the proposed
control method.
