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Improved Fourier transform for processes with initial cyclic‐steady‐state
Author(s) -
Cheon Yu Jin,
Jeon Chun Ho,
Lee Jietae,
Sung Su Whan,
Lee Dong Hyun
Publication year - 2010
Publication title -
aiche journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.958
H-Index - 167
eISSN - 1547-5905
pISSN - 0001-1541
DOI - 10.1002/aic.12068
Subject(s) - steady state (chemistry) , fourier transform , process (computing) , identification (biology) , nonparametric statistics , control theory (sociology) , state (computer science) , function (biology) , computer science , fourier analysis , fourier series , short time fourier transform , discrete fourier transform (general) , mathematics , algorithm , biological system , mathematical analysis , chemistry , statistics , artificial intelligence , botany , control (management) , evolutionary biology , biology , operating system
A new process identification method is proposed to estimate the frequency responses of the process from the activated process input and output. It can extract many more frequency responses and guarantees better accuracy than the previous describing function analysis algorithm. In addition, the proposed method can be applied to the case that the initial part of the activated process data is periodic (cyclic‐steady‐state), which is not possible with any previous nonparametric identification methods using the modified Fourier transform or Fourier analysis. Furthermore, it can incorporate all the cases in which either the initial part is steady‐state and the final part is cyclic‐steady‐state or both the initial and final parts are steady‐state. © 2010 American Institute of Chemical Engineers AIChE J, 2010