access icon free Finite-time H filtering of Markov jump systems with incomplete transition probabilities: a probability approach

This paper concerns the finite-time H filtering of discrete Markov jump system with incomplete transition probabilities which cover the cases of known, uncertain and unknown. To include all possible cases, with the probability viewpoint, a truncated Gaussian distribution is employed to describe them. To ensure the filtering error systems to be finite-time stochastic stable with a prescribed noise attenuation level, sufficient conditions for the H filter design are yielded in terms of solvability of a set of linear matrix inequalities. A numerical example is given to illustrate the effectiveness of the proposed method.

Inspec keywords: H∞ filters; Gaussian distribution; Markov processes; linear matrix inequalities

Other keywords: truncated Gaussian distribution; discrete Markov jump system; finite time H∞ filtering; H∞ filter design; probability approach; finite-time stochastic stable; filtering error systems; linear matrix inequalities; incomplete transition probabilities

Subjects: Filtering methods in signal processing; Markov processes; Algebra; Markov processes; Algebra; Signal processing theory

References

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