Concurrent Learning Adaptive Finite-Time Control for Spacecraft with Inertia Parameter Identification under External Disturbance

This article investigates the postcapture control problem for the combined spacecraft formed after a service spacecraft captures a noncooperative target by manipulators. Two concurrent learning adaptive finite-time controllers are developed to achieve trajectory tracking and inertia parameter identification simultaneously. As a very common uncertainty affecting the spacecraft motion, the external disturbance should be considered, but it is ignored in most studies identifying inertia parameters. In this article, the presented controllers are designed according to the specific knowledge of the external disturbance: one controller is designed based on the disturbance bound that is assumed to be known; the other identifies the disturbance parameters together with the inertia parameters, presupposing that the nonlinearities involved in the external disturbance are known. Both of the two controllers require no a priori knowledge of the mass and inertia matrix of the combined spacecraft and take the input saturation into account. Sufficient conditions to identify inertia parameters are also given with no need of persistent excitation. The convergence of the closed-loop system is proved within the Lyapunov framework. Numerical results show that the proposed controllers can track the desired position and attitude trajectories in finite time, and, at the same time, the inertia parameters converge to their real values.