Robust fault estimation for networked systems

This paper investigates robust fault isolation and estimation of networked systems, where the plant output is transmitted to the estimator through a network channel with limited communication capacity including signal transmission delay, data packet dropout and measurement quantization. A sufficient condition in terms of affine matrix inequality is developed which guarantees the estimation error below a prescribed bound in the presence of polytopic model uncertainties, time-varying signal delay, networked induced data dropout and quantization. Based on this result, an algorithm for robust fault estimation design is developed by the congruence transformation which transforms the nonlinear matrix inequality to a computable linear matrix inequality (LMI). A numerical example demonstrates that the proposed approach is less constraint restrictive than the existing approaches in literature.