Trajectory Tracking Control of Lunar Explorer Operation Robotic Manipulator Based on Fully Actuated System Approach

To accommodate the need for wide-range operations on the lunar surface while minimizing system weight, lunar robotic manipulators are generally designed with slender links and multiple serially connected rotational joints. This paper investigates the trajectory tracking control problem of a multi-degree-of-freedom (DOF) lunar exploration manipulator, taking into account dynamic model uncertainties, variable end-effector loads, and external disturbances. An adaptive control strategy using a radial basis function neural network (RBFNN) is proposed, based on the fully actuated system approach (FASA), to enhance control precision. A detailed manipulator model is built with SolidWorks, MATLAB, and Simscape, and simulations of typical sampling and placement tasks on the lunar surface are given to validate the effectiveness of proposed control method. Simulation results confirm that the controller ensures fast convergence and high tracking accuracy.