This work suggests an intelligent PV solar tracking system based on a single-axis, which is a combination of Artificial Neural Network (ANN) with Fuzzy Logic Controller (FLC). The ANN determines the tracking angle based on the time and geographical inputs, whereas the FLC adjusts the control actions of the DC motor so that it gives the accurate orientation of the panels. A FLC is incorporated to enhance actuator precision and stability. The proposed system was able to achieve a prediction accuracy of 98%, with a MSE value of 0.0012, demonstrating that the prediction of the best tracking angle can be reliably predicted in various environments. Compared to traditional fixed and sensor-based tracking systems, the intelligent tracking system with a single axis provides increased efficiency of solar energy harvesting, increased system stability, and reduced actuator movement.
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This work was supported by ongoing institutional funding. No additional grants to carry out or direct this particular research were obtained.
S.A. Engineering College, 600077, Chennai, Tamil Nadu, India
Divya Prabha Varadharajan
K.S.R. College of Engineering, 637215, Tiruchengode, Tamil Nadu, India
Sathiyasekar Kumarasamy
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Correspondence to Divya Prabha Varadharajan.
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Varadharajan, D.P., Kumarasamy, S. Artificial Intelligence Driven Solar Tracking System for Enhanced Energy Efficiency and Environmental Sustainability. Autom Remote Control 87, 249–260 (2026). https://doi.org/10.1134/S000511792560106X
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DOI: https://doi.org/10.1134/S000511792560106X
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