Neural network-based robust finite-time attitude stabilization for rigid spacecraft under angular velocity constraint

In this paper, the problem of attitude stabilization control of spacecraft under angular velocity constraint is investigated. A state-constrained finite-time attitude control scheme is designed by making full use of the model feature of the quaternion. Based on the homogeneous domination approach, the finite-time stability of the closed-loop system is proved. It proves that the angular velocity can be constrained within the limited range at any time. For the attitude loop dynamics subsystem with external disturbances, based on a radial basis function neural network, an integral terminal sliding mode controller is proposed. Finally, the validity and advantages of the proposed control scheme are demonstrated in the simulation section compared with the other two control methods.