Event-triggered robust distributed state estimation for sensor networks with state-dependent noises

Abstract

This paper is concerned with the event-triggered distributed state estimation problem for a class of uncertain stochastic systems with state-dependent noises and randomly occurring uncertainties over sensor networks. An event-triggered communication scheme is proposed in order to determine whether the measurements on each sensor should be transmitted to the estimators or not. The norm-bounded uncertainty enters into the system in a random way. Through available output measurements from not only the individual sensor but also its neighbouring sensors, a sufficient condition is established for the desired distributed estimator to ensure that the estimation error dynamics are exponentially mean-square stable. These conditions are characterized in terms of the feasibility of a set of linear matrix inequalities, and then the explicit expression is given for the distributed estimator gains. Finally, a simulation example is provided to show the effectiveness of the proposed event-triggered distributed state estimation scheme.

Keywords:

• distributed state estimation
• randomly occurring uncertainties
• state-dependent noises
• sensor networks

Notes

This work was supported in part by the Deanship of Scientific Research (DSR) at King Abdulaziz University of Saudi Arabia [grant number 16-135-35-HiCi]; the National Natural Science Foundation of China [grant number 61329301], [grant number 61374127] and [grant number 61422301]; the Scientific and Technology Research Foundation of Heilongjiang Education Department of China [grant number 12541061] and the Alexander von Humboldt Foundation of Germany.