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Performance monitoring of MPC based on dynamic principal component analysis

Performance monitoring of MPC based on dynamic principal component analysis
Performance monitoring of MPC based on dynamic principal component analysis
A unified framework based on the dynamic principal component analysis (PCA) is proposed for performance monitoring of constrained multi-variable model predictive control (MPC) systems. In the proposed performance monitoring framework, the dynamic PCA based performance benchmark is adopted for performance assessment, while performance diagnosis is carried out using a unified weighted dynamic PCA similarity measure. Simulation results obtained from the case study of the Shell process demonstrate that the use of the dynamic PCA performance benchmark can detect the performance deterioration more quickly compared with the traditional PCA method, and the proposed unified weighted dynamic PCA similarity measure can correctly locate the root cause for poor performance of MPC controller.
6 pages
Tian, Xuemin
5b7f2306-69c1-41c7-8cab-49932ac1ae01
Chen, Gongquan
0ae2584b-f2f0-4fc7-8413-5cb8c5df886f
Cao, Yuping
40cf0d64-d37a-453d-a8df-c4edccc1d531
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Tian, Xuemin
5b7f2306-69c1-41c7-8cab-49932ac1ae01
Chen, Gongquan
0ae2584b-f2f0-4fc7-8413-5cb8c5df886f
Cao, Yuping
40cf0d64-d37a-453d-a8df-c4edccc1d531
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80

Tian, Xuemin, Chen, Gongquan, Cao, Yuping and Chen, Sheng (2011) Performance monitoring of MPC based on dynamic principal component analysis. 18th IFAC World Congress, Italy. 28 Aug - 02 Sep 2011. 6 pages .

Record type: Conference or Workshop Item (Paper)

Abstract

A unified framework based on the dynamic principal component analysis (PCA) is proposed for performance monitoring of constrained multi-variable model predictive control (MPC) systems. In the proposed performance monitoring framework, the dynamic PCA based performance benchmark is adopted for performance assessment, while performance diagnosis is carried out using a unified weighted dynamic PCA similarity measure. Simulation results obtained from the case study of the Shell process demonstrate that the use of the dynamic PCA performance benchmark can detect the performance deterioration more quickly compared with the traditional PCA method, and the proposed unified weighted dynamic PCA similarity measure can correctly locate the root cause for poor performance of MPC controller.

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More information

Published date: August 2011
Additional Information: Event Dates: August 28 - September 2, 2011
Venue - Dates: 18th IFAC World Congress, Italy, 2011-08-28 - 2011-09-02
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 272924
URI: http://eprints.soton.ac.uk/id/eprint/272924
PURE UUID: bc9d5ef8-a973-4099-8b1c-a4cbcd73884f

Catalogue record

Date deposited: 13 Oct 2011 08:51
Last modified: 19 Jul 2019 22:07

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