Fault Reconstruction for a Giant Satellite Swarm Based on Hybrid Multi-Objective Optimization

To perform indicator selection and verification for the on-orbit fault reconstruction of a giant satellite swarm, hybrid multi-objective algorithm is proposed then verified by Monte Carlo analysis. First, according to failure analysis several optimization indicators, such as health state total energy consumption reconstruction, balance fuel consumption, are proposed. Then, fitness function constructed, genetic used optimize objective obtain optimal strategy. Finally, statistically The simulation results not only show algorithm’s validity but also reveal relationship between number faults swarm. From this, maximum faulty satellites allowed in swarm calculated, which significant assessing swarm’s health.