This study proposes a novel adaptive neural dynamic-based hybrid control strategy for stable subsatellite retrieval of two-body tethered satellite systems. The retrieval speed is given analytically, ensuring a libration-free steady state. To mitigate the potential libration motion, a general control input signal is generated by an adaptive neural-dynamic (AND) algorithm and executed by adjusting the retrieval speed and thruster on the subsatellite. To address the limited retrieval speed and improve the control performance, the thruster controller is manipulated according to a novel advanced state fuzzy control law based on higher-order libration states, whereas the remaining control input is allocated to the speed controller. The Lyapunov stability of the control strategy is demonstrated analytically. Numerical simulations validate the proposed control strategy, demonstrating well-allocated control inputs for both controllers and good control performance.

A floating partial space elevator (PSE) is a PSE with a floating main satellite. This work aims to keep the orbital radius of the main satellite of a floating PSE in cargo transposition without the use of thrusts. A six-degree-of-freedom two-piece dumbbell model was built to analyze the dynamics of a floating PSE. By adjusting the climber’s moving speed and rolling of the end body, the main satellite’s orbital radius can be kept. A novel control strategy using a proportional shrinking horizon model predictive control law containing a self-stability modified law is proposed to stabilize both the orbital and libration states to regulate the speed of only the climber. Simulation results validated the proposed control strategy. The system provides a successful approach to the desired equilibrium by the end of the transposition.