DocumentCode :
2409037
Title :
Model reference adaptive control with unknown high-frequency gain
Author :
Lozano, Rogelio ; Moctezuma, Rubén G.
Author_Institution :
Univ. Technol. Compiegne, Heudiasyc, France
fYear :
1992
fDate :
1992
Firstpage :
2756
Abstract :
An indirect model reference adaptive control for minimum-phase linear systems of arbitrary order with unknown high-frequency gain is presented. It is proved that the (modified) estimate of the high-frequency gain has a uniform positive lower bound. The problem has been solved by using the least squares covariance matrix properties to define an appropriate modification of the parameter estimates. The proposed algorithm requires neither signal normalization nor the definition of an augmented error
Keywords :
least squares approximations; linear systems; matrix algebra; model reference adaptive control systems; parameter estimation; indirect model reference adaptive control; least squares covariance matrix properties; minimum-phase linear systems; parameter estimates; uniform positive lower bound; unknown high-frequency gain; Adaptive control; Convergence; Covariance matrix; Discrete time systems; Frequency estimation; Hysteresis; Least squares approximation; Linear systems; Parameter estimation; Programmable control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control, 1992., Proceedings of the 31st IEEE Conference on
Conference_Location :
Tucson, AZ
Print_ISBN :
0-7803-0872-7
Type :
conf
DOI :
10.1109/CDC.1992.371315
Filename :
371315
Link To Document :
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