Design, Modeling, and Experimental Validation of a Dual-Axis Solar Tracking System with Embedded Control and Monocular Vision

The growing demand for renewable energy requires efficient technologies to maximize solar resource utilization. This study presents the development and validation of a novel dual-axis solar tracking system that integrates kinematic modeling, embedded control, and a monocular vision algorithm. Unlike fixed photovoltaic systems, the proposed design dynamically aligns solar panels with the sun’s position using a Denavit–Hartenberg-based model and real-time image analysis. The system was experimentally validated in the Isthmus of Tehuantepec, Mexico, a high-irradiance region. Results showed reliable sensor calibration with errors below 3%, and an 18% increase in energy capture compared to a fixed panel system. The prototype achieved a maximum output of 800 W using four 205 Wp modules. This work contributes an innovative, replicable approach to enhance solar energy harvesting under real operating conditions.