Abstract
The problem of robustH∞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 robustH∞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 guaranteedH∞performance constraint is achieved. Furthermore, the optimalH∞performance index is subsequently obtained by solving a convex optimisation problem and the missing measurements effects on theH∞performance are evaluated. A numerical example is given to illustrate the feasibility and effectiveness of the proposed filter.
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