Recursive Bayesian Algorithm for Identification of Systems with Non-uniformly Sampled Input Data

To identify systems with non-uniformly sampled input data, a recursive Bayesian identification algorithm with covariance resetting is proposed. Using estimated noise transfer function as a dynamic filter, the system with colored noise is transformed into the system with white noise. In order to impr...

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Vydané v:Machine intelligence research (Print) Ročník 15; číslo 3; s. 335 - 344
Hlavní autori: Jing, Shao-Xue, Pan, Tian-Hong, Li, Zheng-Ming
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Beijing Springer Nature B.V 01.06.2018
Predmet:
Algorithms
Automation
Bayesian analysis
Covariance
Estimates
Identification
Kalman filters
Parameter estimation
Transfer functions
White noise
ISSN:2153-182X, 2153-1838
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Abstract To identify systems with non-uniformly sampled input data, a recursive Bayesian identification algorithm with covariance resetting is proposed. Using estimated noise transfer function as a dynamic filter, the system with colored noise is transformed into the system with white noise. In order to improve estimates, the estimated noise variance is employed as a weighting factor in the algorithm. Meanwhile, a modified covariance resetting method is also integrated in the proposed algorithm to increase the convergence rate. A numerical example and an industrial example validate the proposed algorithm.
AbstractList To identify systems with non-uniformly sampled input data, a recursive Bayesian identification algorithm with covariance resetting is proposed. Using estimated noise transfer function as a dynamic filter, the system with colored noise is transformed into the system with white noise. In order to improve estimates, the estimated noise variance is employed as a weighting factor in the algorithm. Meanwhile, a modified covariance resetting method is also integrated in the proposed algorithm to increase the convergence rate. A numerical example and an industrial example validate the proposed algorithm.
Author Li, Zheng-Ming
Pan, Tian-Hong
Jing, Shao-Xue
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CitedBy_id crossref_primary_10_1007_s11633_018_1161_8
crossref_primary_10_1007_s11633_017_1106_7
crossref_primary_10_1016_j_jelechem_2022_116011
crossref_primary_10_1007_s11277_021_08954_7
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Copyright Institute of Automation, Chinese Academy of Sciences and Springer-Verlag GmbH Germany, part of Springer Nature 2017.
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SubjectTerms Algorithms
Automation
Bayesian analysis
Covariance
Estimates
Identification
Kalman filters
Parameter estimation
Transfer functions
White noise
Title Recursive Bayesian Algorithm for Identification of Systems with Non-uniformly Sampled Input Data
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