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Stability of Kalman filter for time‐varying systems with correlated noise
Author(s) -
Li Ruisheng,
Chu Dongsheng
Publication year - 1997
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/(sici)1099-1115(199709)11:6<475::aid-acs438>3.0.co;2-1
Subject(s) - control theory (sociology) , kalman filter , estimator , sense (electronics) , stability (learning theory) , noise (video) , covariance , forgetting , mathematics , recursive least squares filter , computer science , adaptive filter , algorithm , statistics , engineering , control (management) , artificial intelligence , machine learning , electrical engineering , image (mathematics) , linguistics , philosophy
The stability of a Kalman filter based on an adaptive estimator in the time average sense for a time‐varying stochastic system with correlated noise is obtained under a persistent excitation condition. The stabilities of the closed‐loop system and estimating error are established by designing an adaptive control law and restricting the growth rates of input and output signals. The stabilities of the extended least squares algorithm with forgetting factor and with covariance modification in the time average sense and sample average sense respectively are obtained. © 1997 by John Wiley & Sons, Ltd.