Appointed-time prescribed performance control for 6-DOF spacecraft rendezvous and docking operations under input saturation

Abstract

This study investigates the adaptive appointed-time control problem of chaser spacecraft rendezvous and docking with unknown target spacecraft information, parametric uncertainties, external disturbances, input saturation and performance constraints. Two kinds of novel prescribed performance function are first proposed to relax the limitation of the initial values of state signals and the contradiction between input saturation and performance constraints. Using dynamic surface control theory and a novel compensation system, an adaptive anti-saturation appointed-time prescribed performance controller and an adaptive anti-saturation appointed-time neural network-based prescribed performance controller are presented. An auxiliary variable is used to compensate for input saturation. Considering the strong approximation of the radial basis function neural network, an appointed-time neural network-based control scheme is proposed to compensate for external disturbances and parametric uncertainties. All closed-loop states converge to a neighborhood of zero in appointed-time, and the performance constraints of the relative position as well as the relative attitude are satisfied. A number of simulation scenarios are considered to verify the effectiveness of the proposed control strategies.