DocumentCode :
2333217
Title :
Performance assessment of multivariable control systems using PCA control charts
Author :
Chen, Junghui ; Wang, Wei-Yann
Author_Institution :
Dept. of Chem. Eng., Chung-Yaun Christian Univ., Chungli, Taiwan
fYear :
2009
fDate :
25-27 May 2009
Firstpage :
936
Lastpage :
941
Abstract :
In the MIMO system, the benchmark of the multivariable system in the past is computed from the traces of the multivariable covariance matrices. This may cause false detection since the correlation among variables is not considered. In this paper, a new method, called ARMA-PCA based MV, is proposed. It is an integrated framework of multivariable principal component analysis (PCA) and the autoregressive moving average (ARMA) filter for building up the minimum variance (MV) performance bound of the MIMO feedback control system. The benchmark of the multivariable system is achievable by the minimum score of the variances using the resulting decomposition structure of the PCA model without the risk of the overdetermined or underdetermined problems in the MIMO system. After extracting the essential features of the benchmark information, subsequently, improved statistics is selected as the performance benchmark index to monitor the progress of the current operation. The case study indicates that the proposed method yields better monitoring results than the conventional approaches in terms of sensitivity and time to the degraded system.
Keywords :
MIMO systems; autoregressive moving average processes; covariance matrices; feedback; multivariable control systems; principal component analysis; MIMO feedback control system; PCA control chart; autoregressive moving average filter; decomposition structure; multivariable control system; multivariable covariance matrices; multivariable principal component analysis; Autoregressive processes; Control charts; Control systems; Covariance matrix; Data mining; Feedback control; Filters; MIMO; Monitoring; Principal component analysis; Control Loop Performance; Monitoring and Diagnosis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics and Applications, 2009. ICIEA 2009. 4th IEEE Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-4244-2799-4
Electronic_ISBN :
978-1-4244-2800-7
Type :
conf
DOI :
10.1109/ICIEA.2009.5138338
Filename :
5138338
Link To Document :
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