Diagnosis of solar panels using Fuzzy logic with a recursive method

The article presents an innovative methodology for diagnosing faults in solar panels using an approach that combines fuzzy logic and recursive least squares (RLS). The main objective of the study is to develop a robust and accurate diagnostic system capable of detecting and locating faults in solar panels. The proposed method uses fuzzy logic to model the complex relationships between the parameters of the solar panel, such as brightness, temperature, voltage, current, and the operating state of the solar panel. Recursive least squares (RLS) are integrated into the diagnostic system to dynamically update the fuzzy parameters of the model based on new observations and real data from the solar panel. This approach allows continuous adaptation of the diagnostic model to changes in environmental conditions and the operation of the solar panel. The results demonstrate the effectiveness and accuracy of the proposed diagnostic system, with a high capability to detect and locate different types of faults in solar panels.