Title
Recursive Bias-Compensating Algorithm For The Identification Of Dynamical Bilinear Systems In The Errors-In-Variables Framework
Abstract
The paper investigates a recursive approach for the bias compensating least squares (BCLS) technique. The method presented is applied to the problem of on-line identification of single-input single-output bilinear models in the errors-in-variables framework. Within this framework the recursive bilinear BCLS algorithm is realized when a bilinear Frisch scheme (BFS) is iteratively applied for the estimation of the parameters of an exemplary bilinear system, giving rise to the exact recursive BFS (ERBFS) method. Moreover, a further extension of the ERBFS incorporating Tikhonov regularization with variable exponential weighting is considered and this is shown to be beneficial in the initial period of the identification procedure.
Year
Venue
Keywords
2008
ICINCO 2008: PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS, VOL SPSMC: SIGNAL PROCESSING, SYSTEMS MODELING AND CONTROL
bias compensation, bilinear systems, errors-in-variables, recursive estimation, regularization, system identification
Field
DocType
Citations 
Bilinear map,Errors-in-variables models,Bilinear systems,Algorithm,System of bilinear equations,Engineering,Recursion,Bilinear interpolation
Conference
0
PageRank 
References 
Authors
0.34
1
4
Name
Order
Citations
PageRank
Tomasz Larkowski143.14
Jens G. Linden242.80
Benoit Vinsonneau331.42
Keith J. Burnham46213.88