Joint State and Fault Estimation of Complex Networks Under Measurement Saturations and Stochastic Nonlinearities

In this paper, the joint state and fault estimation problem is investigated for a class of discrete-time complex networks with measurement saturations stochastic nonlinearities. The difference between actual saturated regarded as an unknown input system thus re-organized singular system. An appropriate estimator designed each node which aims to estimate states loss actuator effectiveness simultaneously. presence nonlinearities, upper bounds error covariances estimates are recursively obtained then minimized. Sufficient conditions proposed guarantee existence, unbiasedness, boundeness developed estimator. Our design algorithm distributed because it depends only on local information from neighboring nodes, thereby avoiding usage center Finally, simulation results presented show performance strategy in simultaneously estimating faults.