Distributed Simultaneous Fault Estimation and Cluster Consensus Control of Small Satellites

In this study, the distributed fault estimation and control of clusters of satellites with heterogeneous nonlinear dynamics is investigated to determine the magnitude and shape of the unbounded faults in different clusters’ agents while reaching the cluster consensus in the company of faults and external disturbances. In the proposed fault estimation method, an augmented system is constructed for each satellite based on its communication topology to estimate the states and faults of that satellite and all its neighbors. Additionally, the observer used in this approach is an unknown input observer to decouple and minimize the effect of external disturbances on error dynamics. The coefficient matrices are calculated using linear matrix inequalities to reach consensus and estimate the fault simultaneously. Furthermore, to have a robust fault estimation, the
${\mathbf{H}}_\infty $
performance level
${\boldsymbol{\gamma}}$
is selected as an adjustable parameter to improve the state and fault estimation performance. The simulation results are shown for two clusters, including seven small satellites with different disturbances and Lipschitz-based nonlinearities. The results show that by using the proposed approach, the observer implemented in one cluster can estimate the states and faults of satellites in other clusters, minimizing the computational load for large clusters.