Robust Distributed Fault Estimation for a Network of Dynamical Systems

In this paper, the robust distributed fault estimation problem is considered for a network of dynamical systems with external disturbances. Based on local output measurements and state estimates from neighbors, a distributed intermediate estimator is constructed for each node. By spectral decomposition of the Laplacian and proper scalings of the faults and the disturbances, a specially structured global error system can be created. It is proved that the states of the global error system are uniformly ultimately bounded with an explicit error bound. Compared with the existing results, the proposed fault estimation strategy has no requirements of the observer-matching condition and the preliminary knowledge of the upper bounds of the faults; moreover, the robustness of the global error system can be ensured by directly adjusting the design parameters of the intermediate estimators, without introducing any performance specifications. Simulation examples verify the effectiveness of the proposed method.