A Data-Driven Model for Valve Stiction

Choudhury, M.A.A. Shoukat; Thornhill, Nina F.; Shah, Sirish L.

doi:10.1016/s1474-6670(17)38739-6

Cited by 30 publications

(33 citation statements)

References 4 publications

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“…The accuracy of the physical model depends on the understanding of the system characteristics. By contrast with the physical model, the data-driven model of the system can be established only based on the input and output data, which is a "black box model" [11][12][13][14][15]. Developed on the physical model and datadriven model, the semi-physical model is proposed.…”

Section: Of 15mentioning

confidence: 99%

“…Due to the discontinuity point (v = 0) in the friction model, it is not conducive to analyze the established model. To deal with the issue, according to the article [14], a constant ε is introduced to create a very small zone as a mathematical expression of v = 0, i.e., |v| < ε = 10 −4 m/s equals v = 0. Based on the (1)-( 5), the continuous-time model of the pneumatic diaphragm actuator can be obtained:…”

Section: Pneumatic Diaphragm Actuator Modelmentioning

confidence: 99%

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A New Control Method for Backlash Error Elimination of Pneumatic Control Valve

Zhang

2021

Processes

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Backlash is a commonly non-linear phenomenon, which can directly degrade the control accuracy of a pneumatic control valve. To explain the cause and law of backlash error, and to propose an effective method, many research works on the modeling of a pneumatic control valve system have been carried out. The currently model of a control valve system can be classified as a physical model, data-driven model, and semi-physical model. However, most models only consider the force-displacement conversion process of a pneumatic diagram actuator in a pneumatic control valve system. A physical model based on the whole workflow of the pneumatic control valve system is established and a control method to eliminate the backlash error is proposed in this paper. Firstly, the physical model of the pneumatic control valve system is established, which is composed of three parts: pneumatic diaphragm actuator model, nozzle-flapper structure model and electromagnetic model. After that, the input–output relationship of the pneumatic control valve system can be calculated according to the established physical model, and the calculation results are consistent with the experimental result. Lastly, a self-calibration PID (SC-PID) control method is proposed for backlash error elimination. The proposed method can solve valve stem oscillation caused by backlash during valve control.

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Section: Of 15mentioning

confidence: 99%

Section: Pneumatic Diaphragm Actuator Modelmentioning

confidence: 99%

A New Control Method for Backlash Error Elimination of Pneumatic Control Valve

Zhang

2021

Processes

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“…The two parameter data-driven model has been proposed to more accurately capture the dynamics of the valve stiction. The Choudhury model [10] and the Kano model [5] require two parameters: the J and S parameters which represent the size of the stem slip and the combination of the stickband and deadband, respectively, while the He model [6] describes the valve stiction through the parameters f S (static friction band) and f D (kinetic friction band).…”

Section: Stiction Modellingmentioning

confidence: 99%

“…weak stiction,if J1≤Ĵi≤J2 or S1≤Ŝi≤S2 strong stiction,ifĴi>J2 orŜi>S2 (10) where Stiction index (i) is the verdict of valve stiction for data in window i, J i and S i are the estimated J and S of the data in window i, J 1 and J 2 (J 2 > J 1 ) are the thresholds of slip jump for detecting weak and strong stiction respectively, and S 1 and S 2 (S 2 > S 1 ) are the thresholds of deadband plus slip band for detecting weak and strong stiction respectively.…”

Section: Application To Industrial Datamentioning

confidence: 99%

Quantification of Valve Stiction using Particle Swarm Optimisation with Linear Decrease Inertia Weight

Aksornsri

Wongsa

2017

ECTI-CIT

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Valve stiction is one of the most common problems on industrial process control loops. The detection and quantification of valve stiction in control loops is therefore important to ensure the high quality of the products and maintain the reliable performance of control loops. This paper presents an algorithm for quantifying valve stiction in control loop based on linear decrease inertia weight particle swarm optimization to obtain more accurate estimates of stiction parameters. The amount of stiction present in the valve is estimated by identifying parameters of Kano model which is a two-parameter data-driven stiction modelling based on the parallelogram of MVPV phase plot. Simulation results have demonstrated the efficacy of this algorithm in valve stiction quantification and also its robustness to oscillations due to inappropriate controller tuning and external disturbances. Results are confirmed by application to real process industrial data.

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“…O modelamento da válvula de controle de processos pneumática foi proposto por vários dos autores utilizados como referência para este trabalho. Em seus trabalhos, os autores (KAYIHAN; DOYLE III, 2000;CHOUDHURY et al, 2004;GARCIA, 2006GARCIA, , 2008 partem da expressão do somatório de forças para modelar a válvula de controle e suas respectivas forças de atrito, como descrito na Equação (1). Desta forma, chega-se na Equação 2:…”

Section: O Modelo De Atrito De Karnopp E a Válvula De Controleunclassified

Técnicas intrusivas de detecção de atrito em válvulas de controle.

Paiola¹

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Ao querido Professor Claudio Garcia, um exemplo dentro e fora da vida profissional, por toda orientação e paciência que fizeram deste trabalho uma realidade. Aos professores da banca examinadora e aos mestres de cada disciplina cursada durante o mestrado, cujas contribuições foram de grande valia. À minha querida esposa Carol, meu ponto de referência e porto seguro, que abriu tantas concessões quanto possíveis para que este trabalho fosse concretizado. Aos meus queridos pais, Antonio e Ana Maria e irmãs, Renata e Simone, que assim como o resto de minha família, estiveram sempre presentes, me apoiando e suportando durante toda minha vida. Aos meus colegas de pesquisa Gury e Uehara, amigos fiéis e solidários, que muito contribuíram para a conclusão deste estudo. Às empresas em que trabalhei durante o decorrer do meu Mestrado, que me possibilitaram cursar as disciplinas e me ausentar em momentos cruciais. E a todos os amigos não citados mas que, sem sombra de dúvidas, foram muito importantes, direta ou indiretamente, em mais esta conquista de minha vida. VI RESUMO A variabilidade é um problema presente na maioria das malhas de controle de processos industriais, trazendo prejuízo ao causar perda de produtividade e utilização excessiva de matéria prima e energia. Muitas vezes ela é causada pela presença do atrito em válvulas de controle, os atuadores mais usados em processos industriais. Há uma série de métodos propostos para diagnosticar as perturbações causadas pelo atrito nas válvulas, classificados em intrusivos e não-intrusivos. Neste trabalho, foram estudados dois métodos intrusivos. Eles foram aplicados de maneira automática em simulações computacionais, que foram realizadas em um sistema híbrido de teste (HIL) de uma planta de vazão, com dois níveis de atrito da válvula, e também em um ambiente inteiramente simulado, visando analisar o desempenho dos dois métodos. Os resultados obtidos com ambos os métodos foram satisfatórios, muito embora um dos métodos tenha confundido os efeitos gerados pelo atrito com os produzidos por má sintonia do controlador da malha. Palavras-chave: Diagnóstico. Atrito. Atrito estático. Válvula de controle.

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A Data-Driven Model for Valve Stiction

Cited by 30 publications

References 4 publications

A New Control Method for Backlash Error Elimination of Pneumatic Control Valve

A New Control Method for Backlash Error Elimination of Pneumatic Control Valve

Quantification of Valve Stiction using Particle Swarm Optimisation with Linear Decrease Inertia Weight

Técnicas intrusivas de detecção de atrito em válvulas de controle.

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