Recursive resilient filtering for nonlinear stochastic systems with packet disorders

In this paper, a new resilient filtering problem is studied for a class of nonlinear stochastic systems with packet disorders. The underlying system is quite comprehensive that considers both deterministic and stochastic nonlinearities. The phenomenon of packet disorders takes place in the sensor-to-filter channel as a result of the limited capability of the communication network. The random transmission delay, which is the main cause for the packet disorders, is modeled as a bounded random variable obeying a known probability distribution and its influence on the filter performance is examined. Furthermore, the resilient issue of the proposed recursive filter against random fluctuations of the filter gain is thoroughly studied. The purpose of this paper is to develop a resilient filter for the addressed nonlinear stochastic systems such that, in the presence of both stochastic nonlinearities and packet disorders, an upper bound of the filtering error covariance is ensured and then locally minimized through adequate design of the filter gains. Finally, a simulation example is given to illustrate the usefulness of the theoretical results. (c) 2020 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.