ENHANCING SUNFLOWER INSPIRED SOLAR TRACKERS USING ADAPTIVE SIGNAL FILTERING TECHNIQUES
DOI:
https://doi.org/10.62985/j.huit_ojs.vol26.no2E.390Keywords:
Dual axis solar tracker, Kalman filter, Adaptive signal processing, Energy harvesting efficiencyAbstract
Biologically inspired solar trackers that mimic sunflower motion can improve irradiance capture relative to fixed photovoltaic panels, but sensor noise can destabilize low cost light seeking controllers. This paper presents a sunflower inspired dual axis tracker in which four light dependent resistors (LDRs) are combined with a Kalman filter based preprocessing stage before servo actuation. The contribution lies in the integration of a bio inspired folding mechanism with signal conditioning aimed at reducing spurious control updates, rather than in proposing a new filtering algorithm. Prototype tests show that the tracker produces higher charging power than a fixed south facing panel during a 09:00 to 15:00 measurement window, and the filtered signal yields a smoother control reference under transient cloud disturbances. These findings support the feasibility of the design and indicate that adaptive filtering can improve control stability, although long term durability, actuator energy consumption, and full controller comparison remain for future work.
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