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Received October 14, 2003
Accepted January 10, 2004
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This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/bync/3.0) which permits
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Methods for Performance Monitoring and Diagnosis of Multivariable Model-based Control Systems
Dept. of Chemical and Biomolecular Engng, Sogang University, 1-Shinsoodong, Mapogu, Seoul 121-742, Korea
kslee@sogang.ac.kr
Korean Journal of Chemical Engineering, May 2004, 21(3), 575-581(7), 10.1007/BF02705490
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Abstract
Methods for performance monitoring and diagnosis of multivariable closed loop systems have been proposed aiming at application to model predictive control systems for industrial processes. For performance monitoring, the well-established traditional statistical process control method is empolyed. To meet the underlying premise that the observed variable is univariate and statistically independent, a temporal and spatial decorrelation procedure for process variables has been suggested. For diagnosis of control performance deterioration, a method to estimate the model-error and disturbance signal has been devised. This method enables us to identify the cause of performance deterioration among the controller, process, and disturbance. The proposed methods were evaluated through numerical examples.
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Huang B, Shah SL, Kwok EK, "Oh-Line Control Performance Monitoring of MIMO Processes," Proc. ACC, 1250-1254 (1995)
Huang B, "Multivariable Statistical Methods for Control Loop Performance Assessment," Ph.D. Thesis, Univ. of Alberta, Edmonton, Canada (1997)
Kesavan P, Lee JH, Ind. Eng. Chem., 36, 2725 (1997)
Kozub DJ, Garcia CE, "Monitoring and Diagnosis of Automated Controllers in the Chemical Process Industries," 1993 AIChE Annual Meeting, Nov. (1993)
Ljung L, "System Identification: Theory for the User," Prentice-Hall, NJ (1999)
Mamzic CL, "Statistical Process Control," ISA, Research Triangle Park, NC, USA (1995)
Matrikon Homepage, www.matrikon.com (2003)
Vanoverschee P, Demoor B, Automatica, 30(1), 75 (1994)
Ramirez WF, "Computational Methods for Process Simulation," 2nd ed., Butterworth-Heinemann, Boulder, CO (1997)
Qin SJ, Comput. Chem. Eng., 23, 173 (1997)
Qin SJ, Badgwell TA, Control Eng. Practice, 11, 733 (2003)
Stanfelj N, Marlin TE, MacGregor JF, Ind. Eng. Chem., 32, 301 (1993)
