eprintid: 9444
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/94/44
datestamp: 2023-11-09 16:36:05
lastmod: 2023-11-09 16:36:05
status_changed: 2023-11-09 16:29:01
type: conference_item
metadata_visibility: show
creators_name: Jeremiah, S.S.
creators_name: Zabiri, H.
creators_name: Ramasamy, M.
creators_name: Kamaruddin, B.
creators_name: Teh, W.K.
creators_name: Mohd Amiruddin, A.A.A.
title: IAM: An Intuitive ANFIS-based method for stiction detection
ispublished: pub
keywords: Adaptive control systems; Process engineering; Stiction, Adaptive neuro-fuzzy; Case-studies; Control loop; Control performance; In-control; Industrial controls; New approaches, Fuzzy inference
note: cited By 0; Conference of 5th International Conference on Process Engineering and Advanced Materials, ICPEAM 2018 ; Conference Date: 13 August 2018 Through 14 August 2018; Conference Code:143521
abstract: 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. © Published under licence by IOP Publishing Ltd.
date: 2018
publisher: Institute of Physics Publishing
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059421549&doi=10.1088%2f1757-899X%2f458%2f1%2f012054&partnerID=40&md5=47a0de68cdd60388bd5c98f94af41010
id_number: 10.1088/1757-899X/458/1/012054
full_text_status: none
publication: IOP Conference Series: Materials Science and Engineering
volume: 458
number: 1
refereed: TRUE
issn: 17578981
citation:   Jeremiah, S.S. and Zabiri, H. and Ramasamy, M. and Kamaruddin, B. and Teh, W.K. and Mohd Amiruddin, A.A.A.  (2018) IAM: An Intuitive ANFIS-based method for stiction detection.  In: UNSPECIFIED.