relation: https://khub.utp.edu.my/scholars/9444/
title: IAM: An Intuitive ANFIS-based method for stiction detection
creator: Jeremiah, S.S.
creator: Zabiri, H.
creator: Ramasamy, M.
creator: Kamaruddin, B.
creator: Teh, W.K.
creator: 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. © Published under licence by IOP Publishing Ltd.
publisher: Institute of Physics Publishing
date: 2018
type: Conference or Workshop Item
type: PeerReviewed
identifier:   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.     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059421549&doi=10.1088%2f1757-899X%2f458%2f1%2f012054&partnerID=40&md5=47a0de68cdd60388bd5c98f94af41010
relation: 10.1088/1757-899X/458/1/012054
identifier: 10.1088/1757-899X/458/1/012054