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Continuous adaptive observer for state affine sampled‐data systems
Author(s) -
Hann Cheikh A.B.,
AhmedAli Tarek
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.2912
Subject(s) - observer (physics) , affine transformation , control theory (sociology) , nonlinear system , constant (computer programming) , mathematics , sampling (signal processing) , adaptive sampling , state observer , sampling time , computer science , state (computer science) , statistics , algorithm , artificial intelligence , control (management) , computer vision , physics , filter (signal processing) , quantum mechanics , pure mathematics , monte carlo method , programming language
SUMMARY In this paper, a hybrid adaptive observer is designed for a class of nonlinear sampled‐data systems with constant unknown parameters. The proposed observer uses a predictor of the output between the sampling times. This predictor is re‐initialized at each sampling time. This observer is very simple to implement and converges exponentially under some sufficient conditions. An explicit relation between the bound of the maximum allowable sampling time ( τ MASP ) and the parameters of the observer is also given. Copyright © 2012 John Wiley & Sons, Ltd.