H∞ filtering with stochastic sampling

This paper is concerned with the problem of H"~ filtering for continuous-time systems under sampled measurements with probabilistic sampling. It is assumed that the occurrence probabilities of the sampling intervals are given constants and satisfy a Bernoulli distribution. Through a transformation of the discrete time instants, the filtering error system is formulated as a continuous-time system with delays and stochastic parameters. Then, H"~ filter is designed such that the filtering error system is exponentially stable in the mean square, and the L"2-induced gain from the noise signal to the estimation error is guaranteed to be less than a prescribed level. Finally, an example is given to show the effectiveness of the theoretical results.

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