Robust Kalman filter for fractional order systems with uncertain colored noise variance

For fractional order systems with colored process noise, the discretization fractional order system model is used to construct the augmented vector defined by the state vector and colored process noise vector. Based on the augmented equation of fractional order systems, the robust local Kalman filte...

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Bibliographic Details
Main Authors: Guanran Wang, Xiaojun Sun
Format: Article
Language:English
Published: SAGE Publishing 2024-12-01
Series:Measurement + Control
Online Access:https://doi.org/10.1177/00202940241241917
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Summary:For fractional order systems with colored process noise, the discretization fractional order system model is used to construct the augmented vector defined by the state vector and colored process noise vector. Based on the augmented equation of fractional order systems, the robust local Kalman filtering algorithm for fractional order systems with colored process noise is derived. The matrix weighted fusion, weighted measurement fusion and centralized fusion methods were used to fuse and estimate the state of multi-sensor fractional order system. Simulation results show the effectiveness of the proposed algorithm.
ISSN:0020-2940