Performance Assessment and Monitoring of Model Predictive Control Based on Covariance Benchmark

WANG Yuhong; WANG Xuejian

Volume 39 Issue 6

Dec. 2010

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INFORMATION AND CONTROL > 2010 > 39(6): 694-699.

WANG Yuhong, WANG Xuejian. Performance Assessment and Monitoring of Model Predictive Control Based on Covariance Benchmark[J]. INFORMATION AND CONTROL, 2010, 39(6): 694-699.

Citation:

WANG Yuhong, WANG Xuejian. Performance Assessment and Monitoring of Model Predictive Control Based on Covariance Benchmark[J]. INFORMATION AND CONTROL, 2010, 39(6): 694-699.

Citation:

WANG Yuhong, WANG Xuejian. Performance Assessment and Monitoring of Model Predictive Control Based on Covariance Benchmark[J]. INFORMATION AND CONTROL, 2010, 39(6): 694-699.

Performance Assessment and Monitoring of Model Predictive Control Based on Covariance Benchmark

WANG Yuhong^,,
WANG Xuejian

College of Information and Control Engineering, China University of Petroleum, Dongying 257061, China

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Received Date: November 16, 2009
Revised Date: April 19, 2010
Published Date: December 19, 2010

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Abstract

Abstract

For the purpose of performance assessment and monitoring of MPC(model predictive control),a data-based covariance benchmark is adopted in performance assessment and monitoring.Generalized eigenvalue analysis is used to extract corresponding better and worse eigenvectors based on the outputs of the monitored period and benchmark period.The confidence intervals of the eigenvalues on corresponding directions are obtained by using statistical inference method.The performance indices within the isolated better and worse performance subspaces are then derived to assess and monitor the performance of MPC.This measure is successfully applied to performance assessment and monitoring in the Wood-Berry tower process with three mismatch cases.The simulation results show the feasibility and effectiveness of the method.
- covariance benchmark,
- performance assessment,
- performance monitoring,
- model predictive control(MPC),
- model mismatch

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