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Risk-sensitive filtering for jump Markov linear systems
Date
2008-01-01
Author
Orguner, Umut
Demirekler, Muebeccel
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This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
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In this paper, a risk-sensitive multiple-model filtering algorithm is derived using the reference probability methods. First, the approximation of the interacting multiple-model (IMM) algorithm is identified in the reference probability domain. Then, the same type of approximation is used to derive the finite-dimensional risk-sensitive filtering algorithm. The derived algorithm reduces to the IMM filter when the risk-sensitive parameter goes to zero and reduces to the risk-sensitive filter for linear Gauss-Markov systems when the number of models is unity. The algorithm performs better in a simulated uncertain parameter scenario than the IMM filter.
Subject Keywords
Control and Systems Engineering
,
Electrical and Electronic Engineering
URI
https://hdl.handle.net/11511/45833
Journal
AUTOMATICA
DOI
https://doi.org/10.1016/j.automatica.2007.04.018
Collections
Department of Electrical and Electronics Engineering, Article