Distributed Resilient State Estimation for Nonlinear Systems Against Sensor Attacks
Yan Liu, Tao Li, Bo‐Chao Zheng, Mouquan Shen
Abstract
In this article, a distributed resilient state estimation scheme is developed for nonlinear systems under sensor attacks. The scheme is implemented over a multiagent network where each agent utilizes the estimates of local observable system states and the information transmitted from its neighbors to construct a distributed median solver so that the median value of local estimates can be approximately recovered. In order to obtain the estimates of local observable states, the nonlinear function is decomposed and an unknown input observer is designed. Then, by using distributed median solver and differential mean value theorem, the secure state estimation is achieved in a fully distributed way, neither a majority of sensing data nor global information is needed, which is different from the existing results. Finally, simulation results are provided to verify the effectiveness of the proposed method.