Nonparametric Identification of Linear Dynamic Output-errors Systems

This paper deals with the nonparametric identification of linear dynamic systems within an output-error framework. In the system, the input is an arbitrate signal cover a broad enough frequency band, while the output is disturbed by a filtered white noise with unknown variance. Since the full maximu...

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Bibliographic Details
Published in:International journal of control, automation, and systems automation, and systems, 2022-12, Vol.20 (12), p.3932-3939
Main Authors: Sun, Qing, Zou, Siting, Du, Dajun, Fei, Minrui
Format: Article
Language:English
Subjects:
Arbitration
Complexity
Control
Dynamical systems
Engineering
Frequencies
Frequency domain analysis
Frequency response functions
Mechatronics
Nonparametric statistics
Parameter identification
Polynomials
Regular Papers
Robotics
White noise
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Summary:This paper deals with the nonparametric identification of linear dynamic systems within an output-error framework. In the system, the input is an arbitrate signal cover a broad enough frequency band, while the output is disturbed by a filtered white noise with unknown variance. Since the full maximum likelihood method used in the frequency domain causes calculation complexity, this paper develops a nonparametric method to cope with the complexity. According to the property that the frequency response function and the system leakage term can be locally approximated very well via a low-order degree polynomial, a frequency domain estimator is developed, which can obtain the estimates for the frequency response function and the output noise variance. Finally, the parameters identification results for one real model can validate the effectiveness of the new proposed nonparametric method.
ISSN:1598-6446
2005-4092
DOI:10.1007/s12555-020-0401-1