RBF Neural Network-Based Cooperative Electromagnetic Takeover Control for Large-Scale Failed Spacecraft

To achieve precise and smooth docking, this paper proposes a sliding mode control strategy for cooperative electromagnetic takeover involving multiple servicing spacecraft. First, a relative motion dynamics model for electromagnetic takeover between servicing and failed spacecraft is established based on a far-field electromagnetic force model. Next, an intelligent sliding mode controller is developed based on a radial basis function (RBF) neural network. The controller ensures fixed-time convergence and prescribed-time stability, with system stability rigorously proven using Lyapunov theory. Finally, an appropriate communication topology and control parameters are selected to conduct numerical simulations of multiservicing spacecraft for cooperative electromagnetic takeover. Simulation results demonstrate that the proposed RBF neural network-based sliding mode control approach enables high-precision and smooth electromagnetic takeover under strong disturbance conditions, while maintaining the stability of the system’s center of mass throughout the takeover process.