Fault-Tolerant Model Predictive Control for Spacecraft Formations via Nonlinear Regression

This paper introduces a fault-tolerant control (FTC) approach that combines station-keeping and formation reconfiguration in spacecraft formation flying. The study focuses on the nonlinear relative motion dynamics between two spacecraft, taking into account model uncertainties, external disturbances, input saturation, and thruster faults. When a fault occurs, a nonlinear regression method is used to reconstruct the system model from available measurements. This updated model is then used to design a nonlinear model predictive controller (NMPC) capable of maintaining performance despite actuator failures. The proposed method is evaluated under various fault scenarios to assess its stability and effectiveness.