Fault Prediction for Nonlinear System Using Sliding ARMA Combined with Online LS-SVR
Joint Authors
Zhang, Wei
Su, Shengchao
Zhao, Shuguang
Source
Mathematical Problems in Engineering
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-07-16
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
A robust online fault prediction method which combines sliding autoregressive moving average (ARMA) modeling with online least squares support vector regression (LS-SVR) compensation is presented for unknown nonlinear system.
At first, we design an online LS-SVR algorithm for nonlinear time series prediction.
Based on this, a combined time series prediction method is developed for nonlinear system prediction.
The sliding ARMA model is used to approximate the nonlinear time series; meanwhile, the online LS-SVR is added to compensate for the nonlinear modeling error with external disturbance.
As a result, the one-step-ahead prediction of the nonlinear time series is achieved and it can be extended to n-step-ahead prediction.
The result of the n-step-ahead prediction is then used to judge the fault based on an abnormity estimation algorithm only using normal data of system.
Accordingly, the online fault prediction is implemented with less amount of calculation.
Finally, the proposed method is applied to fault prediction of model-unknown fighter F-16.
The experimental results show that the method can predict the fault of nonlinear system not only accurately but also quickly.
American Psychological Association (APA)
Su, Shengchao& Zhang, Wei& Zhao, Shuguang. 2014. Fault Prediction for Nonlinear System Using Sliding ARMA Combined with Online LS-SVR. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-491049
Modern Language Association (MLA)
Su, Shengchao…[et al.]. Fault Prediction for Nonlinear System Using Sliding ARMA Combined with Online LS-SVR. Mathematical Problems in Engineering No. 2014 (2014), pp.1-9.
https://search.emarefa.net/detail/BIM-491049
American Medical Association (AMA)
Su, Shengchao& Zhang, Wei& Zhao, Shuguang. Fault Prediction for Nonlinear System Using Sliding ARMA Combined with Online LS-SVR. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-491049
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-491049