Adaptive coordinated control for space manipulators with input saturation

This paper presents a concurrent learning command filtering control scheme for space manipulators in the post-capture phase. Due to the complex space environment and inherent model characteristics, space manipulators are subject to parameter uncertainties, non-conserved momentum and input saturation, which will degrade the control performance. To this end, a novel fixed-time concurrent learning law is developed in the presence of the non-conserved linear and angular momentum, where the convergence rate of the estimated parameters is determined by the control coefficients rather than the unpredictable excitation level. Then, a fixed-time command filtering strategy with the error compensation and saturation compensation is designed, to cope with input saturation and avoid the derivation operation of Jacobi matrices and inertial matrices simultaneously. By means of the proposed control scheme, the spacecraft attitude regulation error and the end-of-arm trajectory tracking error can converge to the small neighborhood of zeros within a fixed time. Simulation results demonstrate the effectiveness of the proposed control scheme.