An Iterative LMI-Based Approach for Reduced-Order H∞ Filtering of Discrete-Time Hidden Markov Jump Linear Systems

2026-01-01

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Granato, Marco A. *

Costa, Oswaldo L. V.

DOI：10.1109/LCSYS.2026.3654509

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This letter addresses the reduced-order H-infinity filtering problem for discrete-time Markov jump linear systems where the jump parameter cannot be directly measured and only detector-based estimates are available to the filter. Necessary and sufficient synthesis conditions are established in terms of bilinear matrix inequalities, for which a sufficient suboptimal solution is obtained via an iterative approach based on linear matrix inequality. A numerical example illustrates the effectiveness of the method and highlights performance improvements over existing results.

Keywords:

Symmetric matrices

Hidden Markov models

Linear matrix inequalities

Iterative methods

Stochastic processes

Linear systems

Information filters

Detectors

Upper bound

Uncertainty

Reduced-order filtering

hidden Markov models

Markov jump linear systems

LMIs

An Iterative LMI-Based Approach for Reduced-Order H∞ Filtering of Discrete-Time Hidden Markov Jump Linear Systems

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