Determining the state of a process control system: Current trends and future challenges

Shardt, Yuri A.W.; Zhao, Yu; Qi, Fei; Lee, K.; Yu, Xinwei; Huang, Biao; Shah, Sirish L.

doi:10.1002/cjce.20653

Cited by 70 publications

(41 citation statements)

References 202 publications

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“…Among the few surveys including software packages, papers by Shardt et al [111] and Brásio et al [9] should be mentioned. Historically developed for controller re-tuning, nowadays these tools not only detect loops needing attention and/or maintenance but also include different features for a more general diagnosis of loop status.…”

Section: Software Packagesmentioning

confidence: 99%

RETRACTED: Review on Valve Stiction. Part I: From Modeling to Smart Diagnosis

Capaci

Scali

2015

Processes

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Abstract:Valve stiction is indicated as one of the main problems affecting control loop performance and then product quality. Therefore, it is important to detect this phenomenon as early as possible, distinguish it from other causes, and suggest the correct action to the operator in order to fix it. It is also very desirable to give an estimate of stiction amount, in order to be able to follow its evolution in time to allow the scheduling of valve maintenance or different operations, if necessary. This paper, in two parts, is a review of the state of the art about the phenomenon of stiction from its basic characterization to smart diagnosis, including modeling, detection techniques, quantification, compensation and a description of commercial software packages. In particular, Part I of the study analyzes the most significant works appearing in the recent literature, pointing out analogies and differences among various techniques, showing more appealing features and possible points of weakness. The review also includes an illustration of the main features of performance monitoring systems proposed by major software houses. Finally, the paper gives indications on future research trends and potential advantages for loop diagnosis when additional measurements are available, as in newly designed plants with valve positioners and smart instrumentation. In Part II, performance of some well-established methods for stiction quantification are compared by applications to different industrial datasets. OPEN ACCESSProcesses 2015, 3 423

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Section: Software Packagesmentioning

confidence: 99%

RETRACTED: Review on Valve Stiction. Part I: From Modeling to Smart Diagnosis

Capaci

Scali

2015

Processes

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“…The number of embedded vectors, N E , in an embedding matrix is limited by the total number of samples n of the time series according to Equation (3). The incomplete brackets indicate a floor function, which maps a real number to the largest previous integer.…”

Section: Embedding Matrixmentioning

confidence: 99%

“…In the past decade, analysis of disturbances in chemical process systems, for example for detection and diagnosis, has shifted from being focused on single control loops [1] to taking a plant-wide approach [2,3]. This extension made sense because chemical processes are highly interconnected, thus disturbances often propagate throughout the plant along mass and energy flows, and control signals.…”

Section: Introductionmentioning

confidence: 99%

“…Transient disturbances are well known to practitioners in process industries but previous research on data-driven plant-wide analysis methods has tended to focus on persistent disturbances, which are repetitive and last for long time horizons [2,3,13]. Methods for persistent disturbances, however, are not appropriate for transient disturbances because they rely on the repetition of the abnormal dynamic episode [14,15,16,17].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Nearest neighbors method for detecting transient disturbances in process and electromechanical systems

Cecı́lio

Ottewill

Pretlove

et al. 2014

Journal of Process Control

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“…In most industrial process control applications, the inherent (gradual) time-varying nature of the plant dynamics diminishes the lifetime performance of model-based control systems (see MacGregor & Cinar, 2012;Qin, 2012;Yin, Ding, Haghani, Hao, & Zhang, 2012;Shardt et al, 2012 for recent reviews on performance monitoring and diagnosis). Changes in the plant dynamics over time increase the plant-model mismatch, which may eventually invalidate the model identified at the commissioning stage of a model-based control system.…”

Section: Introductionmentioning

confidence: 99%

Least costly closed-loop performance diagnosis and plant re-identification

Mesbah

Bombois

Forgione

et al. 2015

International Journal of Control

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The inherent time-varying nature of dynamics in chemical processes often limits the lifetime performance of model-based control systems, as the plant and disturbance dynamics change over time. A critical step in the maintenance of model-based controllers is distinguishing control-relevant plant changes from variations in disturbance characteristics. In this paper, prediction error identification is used to evaluate a hypothesis test that detects if the performance drop arises from controlrelevant plant changes. The decision rule is assessed by verifying whether an identified model of the true plant lies outside the set of all plant models that lead to adequate closed-loop performance. A unified experiment design framework is presented in the least costly context (i.e., least intrusion of nominal plant operation) to address the problem of input signal design for performance diagnosis and plant re-identification when the performance drop is due to plant changes. The application of the presented performance diagnosis approach to a (nonlinear) chemical reactor demonstrates the effectiveness of the approach in detecting the cause of an observed closed-loop performance drop based on the designed least costly diagnosis experiment.

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Determining the state of a process control system: Current trends and future challenges

Cited by 70 publications

References 202 publications

RETRACTED: Review on Valve Stiction. Part I: From Modeling to Smart Diagnosis

RETRACTED: Review on Valve Stiction. Part I: From Modeling to Smart Diagnosis

Nearest neighbors method for detecting transient disturbances in process and electromechanical systems

Least costly closed-loop performance diagnosis and plant re-identification

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