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Self‐tuning minimum variance control of linear systems followed by saturation nonlinearities in a noisy frame
Author(s) -
Pupeikis Rimantas
Publication year - 2012
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.2888
Subject(s) - control theory (sociology) , nonlinear system , lti system theory , linear system , mathematics , control system , minimum variance unbiased estimator , computer science , engineering , control (management) , mathematical analysis , physics , mean squared error , statistics , electrical engineering , quantum mechanics , artificial intelligence
SUMMARY The aim of the present paper was to increase the efficiency of self‐tuning minimum variance (MV) control of linear systems followed by the so‐called hard nonlinearities. To this end, an approach based on reordering of observations to be processed for the reconstruction of an unmeasurable internal intermediate signal, which acts between a linear dynamic time‐invariant (LTI) system and a static nonlinear block of the closed loop Wiener system with a saturation nonlinearity in an output, has been developed. The technique based on the ordinary least squares and on data partition is used for the internal signal extraction. The results of numerical simulation, identification, and self‐tuning MV control as well as generalized MV control of the second‐order discrete‐time closed loop LTI system with the saturation nonlinearity are given by the computer. Copyright © 2012 John Wiley & Sons, Ltd.