Distributed Fault Estimation for Time-varying Systems with Randomly Occurring Nonlinearities over Sensor Networks

This paper is concerned with the distributed fault estimation problem for a class of time-varying systems which are subject to randomly occurring nonlinearities (RONs) over sensor networks. The random nonlinearities are characterized by random variables obeying certain probabilistic distributions in the interval [0, 1]. And the available output measurements are obtained from both the individual sensor and its neighboring sensors. We aim to design a fault estimator such that the disturbance rejection attenuation level is constrained to a prescribed H-infinity performance index. Conditions which are sufficient are achieved to guarantee that the desired fault estimator satisfies the estimation performance constraint by adopting intensive stochastic analysis. Finally, a numerical example is provided to illustrate the validity of the proposed estimation technique.