Distributed state estimation for periodic systems with sensor nonlinearities and successive packet dropouts

In this paper, distributed state estimators are designed for periodic systems with sensor nonlinearities and successive packet dropouts. In consideration of large quantity of sensor work in harsh environment, the sensor nonlinearities are considered. By using the Bernoulli processes, a new model is introduced to describe the randomly occurred packet dropouts in transmission of neighbors' information. In terms of property of periodic systems, N-periodic distributed state estimators are proposed to estimate the target plant. Then sufficient conditions are established to ensure that the augmented estimation error system is globally asymptotically stable with the prescribed l2−l∞ performance index γ in average sense. Finally, a numerical example is utilized to illustrate the effectiveness of the proposed new method.