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