Precise End-Effector Control for an Aerial Manipulator Under Composite Disturbances: Theory and Experiments

One of inescapable challenges in facilitating the application of aerial manipulators is to achieve the high precision control performance of the end-effector. The manipulator motions beneath the UAV platform constantly contend with composite disturbances, such as floating base, strong inner coupling effects, and model uncertainties. These factors collectively contribute to an inadequate control performance. In this paper, a composite control scheme is presented to tackle this issue. Specifically, a joint velocity planner is proposed to handle the base-floating disturbance in kinematic loop. By virtue of the generated joint reference signal, the base-floating disturbance can be effectively alleviated. The tracking error of the end-effector can be ensured within a small set. Moreover, in a complementary manner, neural network (NN) approximation and nonlinear disturbance observer (NDO) compensation are combined to track the joint references. The NN is adopted to estimate composite dynamic model including inner coupling effects and model uncertainties, while the NDO is designed to handle the remaining uncompensated part. The stability of the closed-loop system including the manipulator kinematics and dynamics is guaranteed using the Lyapunov-like method. Experimental results are reported to manifest the effectiveness of the proposed composite control scheme. Note to Practitioners —This work is driven by the precise end-effector control problem of an aerial manipulator subject to base-floating, strong dynamic coupling, and model uncertainties. Most of existing approaches implicitly address this issue by improving the flight performance of the aerial platform. However, the composite disturbances acted on the manipulator, which would deteriorate the operation accuracy of the end-effector, are not systematically addressed. In this work, a composite control scheme is constructed, which consists of the manipulator joint velocity planner and the dynamic controller. The idea is intuitive. The joint velocity is generated to counteract the fluctuation of the aerial platform. Furthermore, the dynamic controller is developed to accurately track the planned joint velocity in the presence of strong coupling and model uncertainties. The proposed scheme guarantees the stability of the close loop system, making our approach especially promising solution for aerial manipulation under composite disturbances.