%J IOP Conference Series: Materials Science and Engineering
%L scholars9444
%O 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
%N 1
%R 10.1088/1757-899X/458/1/012054
%D 2018
%X 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.
%K Adaptive control systems; Process engineering; Stiction, Adaptive neuro-fuzzy; Case-studies; Control loop; Control performance; In-control; Industrial controls; New approaches, Fuzzy inference
%A S.S. Jeremiah
%A H. Zabiri
%A M. Ramasamy
%A B. Kamaruddin
%A W.K. Teh
%A A.A.A. Mohd Amiruddin
%I Institute of Physics Publishing
%V 458
%T IAM: An Intuitive ANFIS-based method for stiction detection