The growing energy demand and its relation to climate change have driven the search for sustainable alternatives, such as concentrated solar energy. In this context, heliostats play a crucial role by reflecting and concentrating solar light onto a receiver. However, traditional control approaches based on geographical data have limitations. This study introduces an autonomous control system for heliostats that eliminates the need for preloaded geographical data. The approach is based on communication between the heliostat and the solar tracker, with two configuration modes: map calibration and automatic. Centralized and autonomous heliostats are distinguished, with the latter being the focus of the study. Autonomous heliostats have their own control system and can make decisions regarding positioning and safety. The methodology involves a mathematical algorithm that calculates the optimal rotation and tilt of the heliostat to redirect light toward a target. Simulation and physical prototype testing validate a remarkable consistency between simulated and experimental data. A key result is the surprising similarity of 97.9% between the obtained data, validating the algorithm's effectiveness. This study provides a robust approach for designing autonomous heliostat control systems, integrating simulation and experimentation. These results support the algorithm's precision and ability to direct solar radiation effectively. Expanding towards autonomous control and complete heliostat system evaluation facilitates the path toward more efficient and sustainable concentrated solar energy.