2019
DOI: 10.20944/preprints201901.0002.v1
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The Trade-Off between the Controller Effort and Control Quality on Example of an Electro-Pneumatic Final Control Element

Abstract: For many years, the programmable positioners have been widely applied in structures of modern electro-pneumatic final control elements. The positioner consists of an electro-pneumatic transducer, embedded controller and measuring instrumentation. Electro-pneumatic transducers that are used in positioners are characterized by a relatively short mean time-to-failure. The practical and economical method of a reasonable prolongation of this time is proposed in this paper. It is principally based on assessment and … Show more

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Cited by 7 publications
(4 citation statements)
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“…We trained and validated the LLSSVM Hammerstein model for the pH neutralization process with the welltuned parameters. This model meets the lower value of MSE (Mean Squared Error) lesser than 0.5 and a higher value of VAF (variance accounted for) greater than 95% [28].…”
Section: Figure 3 the Ph Neutralization System Input (Base Flow Rate)...supporting
confidence: 55%
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“…We trained and validated the LLSSVM Hammerstein model for the pH neutralization process with the welltuned parameters. This model meets the lower value of MSE (Mean Squared Error) lesser than 0.5 and a higher value of VAF (variance accounted for) greater than 95% [28].…”
Section: Figure 3 the Ph Neutralization System Input (Base Flow Rate)...supporting
confidence: 55%
“…Solving the optimality conditions [28,29] by taking partial differentiation of Equation ( 4) with respect to w, b, ei, and αi as described in Equations ( 5) to ( 8)…”
Section: Llssvm Hammerstein Model Identification Algorithmmentioning
confidence: 99%
“…The GPI index contains two terms; The first term provides the cumulative squared output power error (P ref -P e ) which is used to minimize the controller error over the time [28,29]. Furthermore, the second term gives the cumulative squared of controller effort which is utilized to minimize the mechanical fatigue of the governor system and also optimize the system energy consumption [30][31][32]. Parameter K u in ( 15) is a constant coefficient to determine contribution of the controller efforts on GPI, and is considered equal to 0.005 based on more than 1000 simulation studies.…”
Section: Simulation-based Sensitivity Analysismentioning
confidence: 99%
“…It is understood as controller output. The index shows the output-input signal energy effectiveness of the controller [22].…”
Section: Control Effortmentioning
confidence: 99%