Design and Analysis of the Effect of the Number of Membership Functions on the Accuracy of the Fuzzy Controller in a Sun Tracking System

Purpose: To investigate how the number of rules in the fuzzy controller affects the single-axis solar tracking system's orientation accuracy. Methodology: Design and compare FLC49 and FLC25 controllers, each with different organic rules and functions. To improve the system efficiency by accurately measuring the maximum power point, the controller receives comparison results from the light sensors installed on the solar panels. We study and analyze the controllers, selecting the best one based on the accuracy of the solar panel orientation. Using the FLC output to operate a two-phase SM. Findings: This study developed a sun tracking system using Matlab/Simulink and compared FLC49 and FLC25 controllers. FLC49 performed better in simulations, with lower settling time and overshoot. The number of rules significantly influenced accuracy, and it also showed lower transient ripple magnitudes, accelerating time response. Unique Contribution to Theory, Practice and Policy: The research investigates the effectiveness of rules in a fuzzy controller and recommends the optimal number of windings to achieve precision in controlling a stepper motor. The study explores the use of 49-rule and 25-rule fuzzy logic controllers to control a stepper motor based on LDR sensor inputs. The researchers found that while both controllers had similar steady time error and overshoot, they differed in orientation accuracy, with the 49-roll fuzzy controller being more accurate in orientation. This single-axis solar tracking system optimizes solar energy conversion into electricity.