Extended Stochastic Gradient Identification Method for Hammerstein Model Based on Approximate Least Absolute Deviation
Joint Authors
Xu, Bao-chang
Lin, Zhong-hua
Zhang, Ying-Dan
Xiao, Yu-yue
Source
Mathematical Problems in Engineering
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-06-13
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
In order to identify the parameters of nonlinear Hammerstein model which are contaminated by colored noise and peak noise, the least absolute deviation (LAD) is selected as the objective function to solve the problem of large residual square when the identification data is disturbed by the impulse noise which obeys symmetrical alpha stable ( S α S ) distribution.
However, LAD cannot meet the need of differentiability required by most algorithms.
To improve robustness and to solve the nondifferentiable problem, an approximate least absolute deviation (ALAD) objective function is established by introducing a deterministic function to replace absolute value under certain situations.
The proposed method is derived from ALAD criterion and extended stochastic gradient method.
Due to the differentiability of the objective function, we can get a recursive identification algorithm which is simple and easy to calculate compared with LAD.
The convergence of the proposed identification method is also proved by Lyapunov stability theory, and the simulation experiments show that the proposed method has higher accuracy and stronger robustness than the least square (LS) method in the identification of Hammerstein model with colored noise and impulse noise.
The impact of impulse noise can be restrained effectively.
American Psychological Association (APA)
Xu, Bao-chang& Lin, Zhong-hua& Zhang, Ying-Dan& Xiao, Yu-yue. 2016. Extended Stochastic Gradient Identification Method for Hammerstein Model Based on Approximate Least Absolute Deviation. Mathematical Problems in Engineering،Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1112885
Modern Language Association (MLA)
Xu, Bao-chang…[et al.]. Extended Stochastic Gradient Identification Method for Hammerstein Model Based on Approximate Least Absolute Deviation. Mathematical Problems in Engineering No. 2016 (2016), pp.1-10.
https://search.emarefa.net/detail/BIM-1112885
American Medical Association (AMA)
Xu, Bao-chang& Lin, Zhong-hua& Zhang, Ying-Dan& Xiao, Yu-yue. Extended Stochastic Gradient Identification Method for Hammerstein Model Based on Approximate Least Absolute Deviation. Mathematical Problems in Engineering. 2016. Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1112885
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1112885