A parameter estimation algorithm for nonlinear multivariable systems subject to bounded disturbances

In this note, a robust recursive algorithm is derived for identification of nonlinear multivariable systems with unknown by bounded disturbances. Particular emphasis is given to the design of a weighing matrix that ensures consistency of the estimated parameters with the input-output data and the no...

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Bibliographic Details
Published in:2003 Conference American Control Vol. 4; pp. 3573 - 3578 vol.4
Main Authors: Becis-Aubry, Y., Boutayeb, M., Darouach, M.
Format: Conference Proceeding
Language:English
Published: IEEE 2003
Subjects:
Convergence
Covariance matrix
Ellipsoids
Error correction
MIMO
Noise measurement
Noise robustness
Noise shaping
Parameter estimation
Symmetric matrices
ISBN:9780780378964, 0780378962
ISSN:0743-1619
Online Access:Get full text
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Summary:In this note, a robust recursive algorithm is derived for identification of nonlinear multivariable systems with unknown by bounded disturbances. Particular emphasis is given to the design of a weighing matrix that ensures consistency of the estimated parameters with the input-output data and the noise constraints, and improves convergence properties. Sufficient conditions for local asymptotic convergence of the algorithm are established. The effectiveness of the proposed algorithm is demonstrated through a numerical example.
Bibliography:SourceType-Conference Papers & Proceedings-1
ObjectType-Conference Paper-1
content type line 25
ISBN:9780780378964
0780378962
ISSN:0743-1619
DOI:10.1109/ACC.2003.1244103