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Evaluating the type 2 fuzzy logic controller with multilayer perceptrons for optimal tracking of solar photovoltaic systems

Author

Listed:
  • S Rinesh
  • M Arun
  • S N Kumar
  • C Prajitha
  • A P Senthil Kumar

Abstract

This study proposes the type 2 fuzzy logic controller with genetic algorithm (T2FLC-GA) for optimal tracking of solar photovoltaic (PV) systems. The suggested technique improves the high-power transmission to loads under long-term weather conditions. Genetic algorithms (GAs) are search algorithms that use natural selection and genetic mechanisms to simultaneously find the near-optimal design for control rules and membership functions. The research proposes a control system that uses GA to increase a PV system’s output energy. This system adjusts the spatial angles of the solar panels along the vertical and horizontal axes. The numerical findings illustrate that the suggested T2FLC-GA model increases the accuracy rate of 98.5%, solar tracking rate of 96.5%, overall performance rate of 97.6%, computation cost rate of 10.5%, and power generation rate of 94.5% compared to other existing models.

Suggested Citation

  • S Rinesh & M Arun & S N Kumar & C Prajitha & A P Senthil Kumar, 2025. "Evaluating the type 2 fuzzy logic controller with multilayer perceptrons for optimal tracking of solar photovoltaic systems," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 20, pages 394-403.
    • Handle: RePEc:oup:ijlctc:v:20:y:2025:i::p:394-403.
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    File URL: http://hdl.handle.net/10.1093/ijlct/ctaf016
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