A review of performance monitoring and assessment techniques for univariate and multivariate control systems

Harris, T. J.; Seppala, C.T.; Desborough, Lane

doi:10.1016/s0959-1524(98)00031-6

Cited by 361 publications

(213 citation statements)

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“…Since this ground-breaking study, much research has been focused on the performance assessment of both singleinput single-output (SISO) and multiple-input multipleoutput controllers as well as feedback, forward and cascade controllers, resulting in a large number of publications (Desborough and Harris, 1992;Harris et al, 1996Harris et al, , 1999Harris and Seppala, 2002;Jelali, 2006;Qin and Yu, 2007;AlGhazzawi and Lennox, 2009) in addition to several commercial applications (Desborough and Miller, 2002;Gao et al, 2003). The increasing popularity of model predictive control (MPC) in industrial applications (Qin and Badgwell, 2003) has led to a high demand for the performance monitoring of MPC systems.…”

Section: Introductionmentioning

confidence: 99%

“…The increasing popularity of model predictive control (MPC) in industrial applications (Qin and Badgwell, 2003) has led to a high demand for the performance monitoring of MPC systems. Generally, performance monitoring includes performance assessment and diagnosis, and the task of MPC controller performance monitoring is composed of three steps (Harris et al, 1999):…”

Section: Introductionmentioning

confidence: 99%

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Performance Monitoring of MPC Based on Dynamic Principal Component Analysis

Tian

Chen²,

Cao

et al. 2011

IFAC Proceedings Volumes

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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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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Performance Monitoring of MPC Based on Dynamic Principal Component Analysis

Tian

Chen²,

Cao

et al. 2011

IFAC Proceedings Volumes

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show abstract

“…After that the tuning is addressed. Time and frequency domain performance evaluation can be found in [1,7], and stochastic performance assessment in [9,8].…”

Section: Introductionmentioning

confidence: 99%

Assessing measurements for feedforward control

Petersson

Årzén

Hagglunr

2001

2001 European Control Conference (ECC)

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“…It was developed utilizing a considerable amount of information and collected data on the different types of ships machinery systems, system failures, system indicators, and troubleshooting methods through textbooks, handbooks, and interviews with chief engineers who are the marine experts on ship marine system. Nowadays, maintenance activity in ships is proposed to be developed with GMAO (computer maintenance management system) software (Louit et al, 2009;harris et al, 1999;and Vosniakos and Wang, 1999). To analyze the obtained data with this software, it is evident that for an adequate resolution of each problem, an adequate model selection to determine the time taken for a particular component or system to reach failure is essential, which can in turn lead to wrong conclusions and decisions.…”

mentioning

confidence: 99%