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Identification of dual‐rate systems based on finite impulse response models
Author(s) -
Ding Feng,
Chen Tongwen
Publication year - 2004
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/acs.820
Subject(s) - impulse response , integer (computer science) , finite impulse response , dual (grammatical number) , identification (biology) , computer science , noise (video) , system identification , least squares function approximation , algorithm , impulse (physics) , sampling (signal processing) , parameter identification problem , mathematical optimization , control theory (sociology) , mathematics , model parameter , statistics , artificial intelligence , data modeling , filter (signal processing) , art , database , estimator , image (mathematics) , mathematical analysis , literature , biology , control (management) , quantum mechanics , computer vision , programming language , botany , physics
Abstract Two identification algorithms, a least squares and a correlation analysis based, are developed for dual‐rate stochastic systems in which the output sampling period is an integer multiple of the input updating period. The basic idea is to use auxiliary FIR models to predict unmeasurable noise‐free (true) outputs, and then use these and system inputs to identify parameters of underlying fast single‐rate models. The simulation results indicate that the proposed algorithms are effective. Copyright © 2004 John Wiley & Sons, Ltd.