Bias compensation methods for stochastic systems with colored noise

For ARX-like systems, this paper derives a bias compensation based recursive least squares identification algorithm by means of the prefilter idea and bias compensation principle. The proposed algorithm can give the unbiased estimates of the system model parameters in the presence of colored noises,...

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Bibliographic Details
Published in:Applied mathematical modelling 2011-04, Vol.35 (4), p.1709-1716
Main Authors: Zhang, Yong, Cui, Guimei
Format: Article
Language:English
Subjects:
Algorithms
Applied sciences
ARX-like systems
Bias
Bias compensation principle
Compensation
Computer science
control theory
systems
Control theory. Systems
Exact sciences and technology
Least squares
Least squares method
Mathematical models
Modelling and identification
Noise
On-line systems
Parameter estimation
Recursive
Recursive identification
Stochastic systems
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Summary:For ARX-like systems, this paper derives a bias compensation based recursive least squares identification algorithm by means of the prefilter idea and bias compensation principle. The proposed algorithm can give the unbiased estimates of the system model parameters in the presence of colored noises, and can be on-line implemented. Finally, the advantages of the proposed bias compensation recursive least squares algorithm are shown by simulation tests.
ISSN:0307-904X
DOI:10.1016/j.apm.2010.10.003