Adaptive Neural Zeta-Backstepping Tracking Control of Rigid Spacecraft with Predefined Damping Ratios

An important issue of attitude tracking of rigid spacecraft when exists inertial uncertainty and external perturbations is studied in this work. Different from the traditional backstepping method, a novel adaptive neural network zeta-backstepping method is proposed, which can realize the predefined adjustment of the system damping ratio through selecting specific controller parameters according to designed rules. At the same time, a second-order Lyapunov function method is introduced in order that system stability is guaranteed. With prescribed damping ratio, the system attitude tracking error will converge to a tiny region close to a state of equilibrium. Finally, simulation results prove the validity of the put-forward control strategy.