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This is a Quantitative Study study.

September 12, 2025

Robust filtering in discrete stochastic systems with jump parameters and interval uncertainty

Key Points

The robust filtering algorithm effectively estimates states in the presence of interval uncertainty and jump parameters.
Using the Kalman filtering schemes, the algorithm accommodates variability through independent uniform random variables.
This method addresses filtering challenges in discrete stochastic systems versus fixed parameter approaches, highlighting its adaptability.
Overall, the approach demonstrates the utility of probabilistic models for better performance in complex systems with variability.

Abstract

A robust filtering algorithm for a discrete stochastic system with interval parameters depending of the hidden Markov chain is considered. To represent the interval parameters, a probabilistic approach is used, which is based on the replacement of indeterminate interval-type parameters with independent random variables with a uni-form distribution. Recurrent Kalman filtering schemes and algorithms for estimating the state of jump parameter are used. An example is provided to illustrate the proposed approach.

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