Adaptive neural dynamic-based hybrid control strategy for stable retrieval of tethered satellite systems

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.