A Self-Tuning Fuzzy PID Controller for SEPIC Based on Takagi-Sugeno Inference System

Abstract

This research paper presents the design and simulation of the proportional integral derivative (PID) controller whose gains are controlled by an adaptive fuzzy tuning mechanism based on a Takagi-Sugeno (TS) inference system to alleviate the computational burden. The classic PID controller is of linear nature which reduces the operational performance of the DC-DC single-ended primary-inductor converter (SEPIC). To address this problem, the self-tuning fuzzy PID controller (STFPID) is designed for SEPIC for photovoltaic systems (PV) to control the duty cycle applied to the switching element of the converter. Comparative performance analysis of fuzzy tuned PID controller in comparison with the conventional PID controller is performed on MATLAB/SIMULINK environment using Fuzzy Logic Toolbox. The use of the self-tuning fuzzy logic PID controller achieved better performance than the conventional linear PID controller under input disturbances and different loads, in terms of maintaining constant output reference voltage, substantially reducing rise and settling time and overshoot.