Sliding mode mean-module filter design for polynomial systems

This paper addresses the mean-module filtering problem for a stochastic polynomial system with Gaussian white noises. The obtained solution contains a sliding mode term, signum of the innovations process. It is shown that the designed sliding mode filter generates the mean-module estimate, which yields a better value of the mean-module criterion in comparison to the mean-square polynomial filter. The theoretical result is complemented with an illustrative example verifying performance of the designed filter, which is compared to the mean-square polynomial filter. The simulation results confirm an advantage in favor of the designed sliding mode filter.

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