Comparative metaheuristic PID tuning for a nonlinear dual-axis solar tracker : simulation and experimental validation

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Taha, Mohamed Ibrahem and Said, Ehab and Elmayyah, Wael and Kamel, Mohamed A.; (2026) Comparative metaheuristic PID tuning for a nonlinear dual-axis solar tracker : simulation and experimental validation. In: 2026 ICEENG International Conference for Innovations in Power and Control Systems (IPCS). IEEE, Piscataway, NJ. ISBN 9798331546991 (https://doi.org/10.1109/IPCS69631.2026.11604194)

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Abstract

This paper proposes a comparative framework for tuning a Proportional-Integral-Derivative (PID) controller in a nonlinear dual-axis solar tracking system (DASTS) using metaheuristic optimization algorithms. First, a mathematical model of the DASTS is derived, including solar position computation, irradiance estimation, nonlinear electromechanical dynamics with gravitational torque, and photovoltaic module modeling. Then the PID controller is optimized using the Integral Time-weighted Absolute Error (ITAE) criterion, where four algorithms–Grey Wolf Optimizer (GWO), Aquila Optimizer (AO), Manta Ray Foraging Optimization (MRFO), and Harris Hawks Optimization (HHO)–are applied. The algorithms are evaluated over 30 independent runs to ensure solution stability. Moreover, a laboratory prototype is developed for real-time experimental validation of tracking accuracy and power generation. Results show similar best responses, where AO, MRFO, and HHO achieve an ITAE of 0.16483, while GWO achieves 0.16488, while statistical analysis confirms that MRFO provides the most robust performance, with a mean ITAE of 0.16491, standard deviation of 0.00017, mean iteration count of 27.567, and execution time of 0.54482 s. The DASTS improves output energy by 30.15% compared to a fixed PV panel.

ORCID iDs

Taha, Mohamed Ibrahem, Said, Ehab, Elmayyah, Wael ORCID logoORCID: https://orcid.org/0000-0003-3302-0342 and Kamel, Mohamed A.;
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