Event-based finite-time H∞ filtering of discrete-time singular jump network systems

Abstract

This article presents the analysis and design problems of event-based (EB) finite-time (FT) 𝐻∞ filtering for discrete-time singular Markov jump network systems (SMNSs) based on separation of matrix inequality variables. According to the EB method, an SMNS model of network-induced delay is introduced. Sufficient conditions of singular stochastic FT boundedness are then obtained for the augmented SMNS model by applying a stochastic Lyapunov functional and introducing slack matrix variables. In addition, using separation schemes for decoupling matrix inequality variables, the EBFT 𝐻∞ filter gain matrices and triggered ones are co-designed to ensure that the augmented SMNSs are singularly stochastic FT bounded with a prescribed performance index. Finally, a practical DC test example is presented to show effectiveness of the proposed approach.