TY  - JOUR
EP  - 124
SN  - 17265479
N1  - cited By 1
TI  - Development and implementation of hybrid controllers for flow control application
SP  - 110
AV  - none
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84879759510&partnerID=40&md5=94fd202e50ef0201b0f738814c6a063c
A1  - Ab Ghafar, M.I.
A1  - Ibrahim, R.
A1  - Mazlan, Z.
JF  - Sensors and Transducers
VL  - 17
Y1  - 2012///
IS  - SPL 12
N2  - The main objective of this paper is to design and implement Hybrid Controllers, which consist of Adaptive Fuzzy PID Controller (AFPIDC) and Adaptive Neuro-Fuzzy Inference System (ANFIS) for flow control application. The implementation has been accomplished onto mobile pilot plant for flow control process unit. Currently, controlling and tuning is done via KONICS PID controller that is mounted on the local control panel. However, it is unable to provide adequate response and need to be manually tuned. Thus, the AFPIDC and ANFIS are developed and implemented as alternatives to the existing PID controller with the capability of Human Machine Interface (HMI) using MATLAB/Simulink. For AFPIDC, Fuzzy Logic reasoning is used to produce adaptive PID gain while for ANFIS; Fuzzy Logic will be tuned by using Artificial Neural Network (ANN) algorithm. Overall, the control performances for PID, AFPIDC and ANFIS will be compared and analyzed for flow control application. © 2012 IFSA.
KW  - Adaptive fuzzy pid controllers; Adaptive neuro-fuzzy inference system; ANFIS; Design and implements; Fuzzy logic controllers; Fuzzy logic reasoning; Human Machine Interface; PID controllers
KW  -  Electric control equipment; Flow control; Fuzzy logic; Neural networks; Pilot plants; Proportional control systems; Three term control systems
KW  -  Controllers
ID  - scholars2434
ER  -