Robust Estimation for Discrete-Time Markovian Jump Linear Systems in a Data Fusion Scenario

Authors

  • Gildson Queiroz de Jesus Programa de Pós-Graduação em Modelagem Computacional em Ciência e Tecnologia, Departamento de Ciências Exatas e Tecnológicas, Universidade Estadual de Santa Cruz, Ilhéus, BA, Brasil https://orcid.org/0000-0003-0831-607X
  • Bruno Martins Calazans Silva Programa de Pós-Graduação em Modelagem Computacional em Ciência e Tecnologia, Departamento de Ciências Exatas e Tecnológicas, Universidade Estadual de Santa Cruz, Ilhéus, BA, Brasil https://orcid.org/0000-0003-4731-4018

DOI:

https://doi.org/10.22481/intermaths.v3i1.10715

Keywords:

Markovian Systems, Data Fusion, Robustness, Kalman Filter

Abstract

This paper considers the problem of robust recursive estimation for discrete-time Markovian jump linear systems in both weighted and probabilistic data fusion scenarios. The problem is stated in terms of the optimization of an appropriate quadratic functional in a data fusion scenario. The estimates presented here were developed based on systems with more than one measurement equation. Numerical examples are presented to verify the effectiveness of proposed algorithms.

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References

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Published

2022-06-30

How to Cite

Queiroz de Jesus, G., & Martins Calazans Silva, B. . (2022). Robust Estimation for Discrete-Time Markovian Jump Linear Systems in a Data Fusion Scenario. INTERMATHS, 3(1), 17-36. https://doi.org/10.22481/intermaths.v3i1.10715

Issue

Vol. 3 No. 1 (2022)

Section

Artigos

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