Controller performance assessment by frequency domain techniques

Kendra, Scott J.; Çınar, Ali

doi:10.1016/s0959-1524(96)00027-3

Cited by 42 publications

(18 citation statements)

References 9 publications

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“…Harris (1989) showed that the minimum variance achievable, with a MVC, can be computed from routine operating data if the process time delay is known. Since then, there has been a multitude of research articles that consider important extensions (Desborough and Harris, 1992;Stanfelj et al, 1993;Huang et al, 1997), alternate benchmarks (Tyler and Morari, 1996;Kendra and Cinar, 1997;Swanda and Seborg, 1999), applications (Thornhill et al, 1999) and industrial perspectives (Kozub, 1996;Desborough and Miller, 2001) on this topic. The user is also referred to the exceptional coverage provided by Huang and Shah (1999) and Qin (1998) to this topic.…”

Section: Estimation Of Variance Reductionmentioning

confidence: 99%

Estimation of Variance Reduction Opportunities Through Cascade Control

et al. 2008

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We describe an approach that is useful in deciding if significant benefits, in terms of control loop performance index (through variability reduction), will be achieved by a change in control loop configuration from simple feedback (SFB) to cascade control. The problem is considered in a stochastic setting and solved using the variance decomposition technique. The proposed methodology requires only routine operating data from an existing simple feedback control loop and knowledge of the process delays. Several simulation examples and one experimental case study exemplify the utility of this approach.

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Section: Estimation Of Variance Reductionmentioning

confidence: 99%

Estimation of Variance Reduction Opportunities Through Cascade Control

et al. 2008

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“…In [21] Kendra and Cinar discuss a method used to estimate the closed loop transfer function of a system by exciting the reference input with a zero mean, pseudo random binary sequence and observing the process output and error response. Performance assessment is based on the comparison between the observed frequency response characteristics and the design specifications.…”

Section: Figure (3) Plot Illustrating the Maximum Closed Loop Log Momentioning

confidence: 99%

Control loop performance assessment: a classification of methods

O’Connor¹,

O’Dwyer²

2004

Irish Signals and Systems Conference 2004

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“…These approaches include the multiple variable system evaluation method based on system identification [13] and statistical hypothesis-based method of examining the reason for deterministic performance deviation [14]. Miao employed an autocorrelation function to monitor control performance [15].…”

Section: Introductionmentioning

confidence: 99%