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Self‐tuning Smith predictors for processes with long dead time
Author(s) -
Hang ChangChieh,
Wang Qingguo,
Cao LiSheng
Publication year - 1995
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.4480090304
Subject(s) - smith predictor , relay , control theory (sociology) , dead time , process (computing) , nyquist plot , controller (irrigation) , computer science , pid controller , nyquist–shannon sampling theorem , fast fourier transform , nyquist stability criterion , simple (philosophy) , autocorrelation , algorithm , mathematics , control (management) , engineering , control engineering , statistics , artificial intelligence , physics , power (physics) , dielectric spectroscopy , temperature control , biology , operating system , quantum mechanics , agronomy , electrochemistry , computer vision , parametric statistics , electrode , philosophy , epistemology
Abstract A simple relay feedback auto‐tuning method is proposed for the Smith predictor, an advanced controller for processes with long dead time. the relay feedback control gives information on one point of the Nyquist curve in terms of ultimate gain and frequency. With an additional measurement of the static gain, a reduced order process model in terms of a first‐ or second‐order dynamics plus dead time could be computed and used to auto‐tune the Smith predictor. When the process dynamics changes more frequently, a self‐tuning controller is required. In this case the Fast Fourier Transform technique can be further employed to track the points on the Nyquist curve by estimating the process frequency response and then used to update the Smith predictor. Excellent performance of the auto‐tuned and self‐tuned Smith predictor has been substantiated by simulations.