DEVELOPMENT AND IMPLEMENTATION OF ADAPTIVE FUZZY PID CONTROLLER (AFPIDC) FOR FLOW CONTROL APPLICATION

In general, this project aims to enhance the capability of conventional PID controller by
designing and implementing the Adaptive Fuzzy Logic PID Controller (AFPIDC) and
compare its performance with the conventional Fuzzy Logic Controller (FLC) for Flow
Control Application in the process plant. The implementation has been done onto the
PeA SimExpert Mobile Pilot Plant SE231B-21 Flow Control and Calibration Process
Unit. This mobile plant consists of several flow measurements which are Orifice,
Coriolis and Vortex Flow Meter. Currently, controlling and tuning is done via KONJCS
PID controller that is mounted on the local control panel. However, current PID
controller does not provide faster response and need to be manually tuned. Thus, the
AFPIDC will be developed and implemented to compare with the existing PID
controller and to design a DCS-HMI interface using MATLAB/Simulink for this pilot
plant. The required hardware tools for this project will be USB-1208 FS Personal
Measurement Device and MATLAB product family. The Fuzzy Inference System (FIS)
are developed using Mamdani Approach. This involves designing and tuning of the
membership functions, input/output rules and the de-fuzzification technique. Fuzzy
Logic reasoning is used to produce adaptive PID gain that will be added up with the
initial PID gain. Overall, the control performances of each controller (PID, FLC and
AFPIDC) will be compared and analyzed for flow control application.