An Improved Generalized Predictive Control in a Robust Dynamic Partial Least Square Framework
Joint Authors
Xin, Jin
Qinghua, Chi
Kangling, Liu
Jun, Liang
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-10-22
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
To tackle the sensitivity to outliers in system identification, a new robust dynamic partial least squares (PLS) model based on an outliers detection method is proposed in this paper.
An improved radial basis function network (RBFN) is adopted to construct the predictive model from inputs and outputs dataset, and a hidden Markov model (HMM) is applied to detect the outliers.
After outliers are removed away, a more robust dynamic PLS model is obtained.
In addition, an improved generalized predictive control (GPC) with the tuning weights under dynamic PLS framework is proposed to deal with the interaction which is caused by the model mismatch.
The results of two simulations demonstrate the effectiveness of proposed method.
American Psychological Association (APA)
Xin, Jin& Qinghua, Chi& Kangling, Liu& Jun, Liang. 2015. An Improved Generalized Predictive Control in a Robust Dynamic Partial Least Square Framework. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-14.
https://search.emarefa.net/detail/BIM-1075072
Modern Language Association (MLA)
Xin, Jin…[et al.]. An Improved Generalized Predictive Control in a Robust Dynamic Partial Least Square Framework. Mathematical Problems in Engineering No. 2015 (2015), pp.1-14.
https://search.emarefa.net/detail/BIM-1075072
American Medical Association (AMA)
Xin, Jin& Qinghua, Chi& Kangling, Liu& Jun, Liang. An Improved Generalized Predictive Control in a Robust Dynamic Partial Least Square Framework. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-14.
https://search.emarefa.net/detail/BIM-1075072
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1075072