Nowadays, renewable energy such as solar power has become important for electricity generation, and solar power systems have been installed in homes. Furthermore, solar tracking systems are being continuously improved by researchers around the world, who focus on achieving the best design and thus maximizing the efficiency of the solar power system. In this project, a fuzzy logic controller has been integrated and implemented in a medium-scale solar tracking system to achieve the best real-time orientation of a solar PV panel toward the sun. This project utilized dual-axis solar tracking with a fuzzy logic intelligent method. The hardware system consists of an Arduino UNO microcontroller as the main controller and Light Dependent Resistor (LDR) sensors for sensing the maximum incident intensity of solar irradiance. Initially, two power window motors (one for the horizontal axis and the other for the vertical axis) coordinate and alternately rotate to scan the position of the sun. Since the sun changes its position all the time, the LDR sensors detect its position at five-minute intervals through the level of incident solar irradiance intensity measured by them. The fuzzy logic controller helps the microcontroller to give the best inference concerning the direction to which the solar PV panel should rotate and the position in which it should stay. In conclusion, the solar tracking system delivers high efficiency of output power with a low power intake while it operates.
Fuzzy logic controller for predictive vision-based target tracking with an unmanned aerial vehicle
