Reactionless control of free-floating space manipulators with parameter uncertainty and input disturbance

This paper studies the control problem of free-floating space manipulators, and a control scheme is proposed to solve reactionless control of the end-effector pose tracking with parameter uncertainty and input disturbance. First, based on dual modeling to treat the end-effector as a virtual base spacecraft, the dynamics with uncertainties are established which map the joints' torque to the end-effector pose and base spacecraft attitude, while the inverse kinematics and the derivative of the generalized Jacobi matrix can be avoided in controller design. Then, the reference acceleration stabilization schemes satisfying prescribed performance constraints are carefully designed for tracking errors, and based on these schemes the steady-state and transient performance of the tracking control can be guaranteed. Further, the radial basis function neural network is adopted to estimate modeling errors caused by parameter uncertainty and input disturbance. In addition, a concurrent learning method is introduced in the network weights matrix update law, which allows the estimation errors to converge a neighborhood of zeros without the need for satisfying the persistent excitation condition. The simulation results verify the effectiveness of the proposed control scheme.