DocumentCode :
1164722
Title :
Singularity-free multivariable model reference adaptive control
Author :
Moctezuma, Rubeén G. ; Lozano, Rogelio
Author_Institution :
CNRS, Univ. de Technol. de Compiegne, France
Volume :
39
Issue :
9
fYear :
1994
fDate :
9/1/1994 12:00:00 AM
Firstpage :
1856
Lastpage :
1860
Abstract :
In this paper we propose a way to solve the problem of singularities in model reference adaptive control of linear multi-input-multi-output (MIMO) systems using a parameter modification procedure based on the least squares covariance matrix inverse. The scheme does not require any explicit prior knowledge about the leading coefficient matrix associated with the control input and secures a uniform lower bound for the determinant of the estimate of this matrix. A global convergence analysis is presented
Keywords :
adaptive control; convergence of numerical methods; least squares approximations; matrix algebra; model reference adaptive control systems; multivariable control systems; MIMO systems; coefficient matrix; global convergence; least squares covariance matrix inverse; lower bound; model reference adaptive control; parameter modification; singularity-free multivariable MRAC; Adaptive control; Convergence; Covariance matrix; Frequency estimation; Least squares methods; MIMO; Matrix decomposition; Parameter estimation; Transfer functions; Upper bound;
fLanguage :
English
Journal_Title :
Automatic Control, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9286
Type :
jour
DOI :
10.1109/9.317112
Filename :
317112
Link To Document :
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