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This paper is concerned with the problem of H ∞ filtering for discrete-time Markov jump linear system with parametric uncertainties and quantized measurements, when the jumping mode information is not accessible. By converting the quantized errors into a sector-bounded nonlinearity, the parametric uncertainties and measurements quantization are dealt with in a unified framework. The mode-independent H ∞ filter is designed, and sufficient conditions are established via Lyapunov function approach, such that for all possible uncertain parameters and quantization errors, the resulting filtering error system is robustly stochastically stable and achieves a guaranteed H ∞ filtering error performance index. A numerical example is provided to demonstrate the feasibility and effectiveness of the proposed approach. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The problem of robust H∞ filtering is investigated for discrete-time Markov jump linear system (DMJLS) with uncertain parameters and missing measurements. The missing measurements process is modelled as a Bernoulli distributed sequence. A robust H∞ filter is designed and sufficient conditions are established in terms of linear matrix inequalities via a mode-dependent Lyapunov function approach, such that, for all admissible uncertain parameters and missing measurements, the resulting filtering error system is robustly stochastically stable and a guaranteed H∞ performance constraint is achieved. Furthermore, the optimal H∞ performance index is subsequently obtained by solving a convex optimisation problem and the missing measurements effects on the H∞ performance are evaluated. A numerical example is given to illustrate the feasibility and effectiveness of the proposed filter. [ABSTRACT FROM AUTHOR]