DESIGN AND PERFORMANCE ANALYSIS OF AN LDR-BASED DUAL-AXIS SOLAR TRACKING SYSTEM INTEGRATED WITH FUZZY LOGIC MPPT

Abstract

Fixed photovoltaic (PV) panels lose significant energy to the sun's continuous angular shift of approximately 15° per hour, typically limiting stationary-panel efficiency to about 25%. This paper presents the design, structural validation, and simulated electrical performance of a low-cost dual-axis solar tracking system that combines quadrant-based light-dependent-resistor (LDR) sensing with a fuzzy-logic maximum power point tracking (MPPT) controller. Four LDRs arranged in an east-west-top-bottom quadrant configuration feed an Arduino UNO, which drives two 12 V DC gear motors to keep the panel normal to incident sunlight. The supporting aluminum structure was validated using finite element analysis (FEA) in ANSYS 19.2, showing a maximum deformation of 0.70 mm and a maximum stress of 27.19 MPa under a 30 N test load — well within allowable material limits, with deformation onset predicted only at 72× the applied load. On the electrical side, a fuzzy logic controller was designed and simulated in MATLAB/Simulink to regulate a DC-DC boost converter for maximum power point tracking. Under fixed test conditions (25°C, 1000 W/m² irradiance), the fuzzy MPPT controller increased output power from 135.2 W to 195.0 W — a 44.2% improvement — compared to the uncontrolled baseline, while also outperforming the conventional Perturb-and-Observe method in convergence speed and steady-state oscillation. Combined, the mechanical tracking and electrical MPPT stages address power optimization from two complementary directions: physical orientation and electronic operating-point control. The results indicate that this dual-layer approach offers a practical, low-cost pathway to meaningfully higher PV yield for small-to-medium-scale installations.