IAM: An Intuitive ANFIS-based method for stiction detection

IAM: An Intuitive ANFIS-based method for stiction detection

Stiction in control valves is an industry-wide problem which results in degradation of control performance. A new approach to detect the presence of stiction by utilising only the PV-OP data from control loops is proposed using an Adaptive Neuro-fuzzy Inferencing System (ANFIS). Intuitively, the err...

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Veröffentlicht in:IOP conference series. Materials Science and Engineering 2018-12, Vol.458 (1), p.12054
Hauptverfasser: Jeremiah, Sean S, Zabiri, H, Ramasamy, M, Kamaruddin, B, Teh, W K, Mohd Amiruddin, A A A
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Adaptive control
Fuzzy logic
Stiction
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container_start_page 12054
container_title IOP conference series. Materials Science and Engineering
container_volume 458
creator Jeremiah, Sean S
Zabiri, H
Ramasamy, M
Kamaruddin, B
Teh, W K
Mohd Amiruddin, A A A
description Stiction in control valves is an industry-wide problem which results in degradation of control performance. A new approach to detect the presence of stiction by utilising only the PV-OP data from control loops is proposed using an Adaptive Neuro-fuzzy Inferencing System (ANFIS). Intuitively, the error between the output of an FIS model developed with stiction and a process with stiction would be minimal. When benchmarked against seventeen well-known industrial control loop case studies, the Intuitive ANFIS-based Method (IAM) accurately predicts the presence or absence of stiction in 65% of loops tested.
doi_str_mv 10.1088/1757-899X/458/1/012054
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subjects Adaptive control
Fuzzy logic
Stiction
title IAM: An Intuitive ANFIS-based method for stiction detection
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