Modeling and simulation of hybrid fuzzy-PID and model predictive control for enhanced dual-axis photovoltaic tracking precision

This paper presents a comprehensive evaluation of several control strategies for dual-axis solar tracking systems, including proportional–integral–derivative , fuzzy logic, fuzzy–PID, and fuzzy–PID enhanced with model predictive control. Each controller was implemented in MATLAB/Simulink to analyse its dynamic and steady-state behaviour under identical conditions. The findings reveal that hybrid and MPC-based controllers achieve superior tracking precision and response smoothness compared to single-loop designs. Specifically, the fuzzy-tuned PID exhibits the fastest rise time of 12.53 but with a higher overshoot of 18.45%. In contrast, the standalone fuzzy controller offers superior stability with a minimal overshoot of 0.50%, though at the expense of slower dynamics with a rise time of 91.81 . The proposed MPC–Fuzzy–PID Series hybrid achieves a rapid rise time of 16.02 and a settling time of 0.2 providing a balanced trade-off between speed, stability, and computational efficiency, making it suitable for real-time solar tracking applications. Overall, the study demonstrates that controller performance depends on the specific operational goals whether prioritizing rapid response, precision, or robustness highlighting the importance of adaptive hybrid control design in sustainable energy systems. • Fuzzy-tuned PID has the fastest rise time and shortest settling time • Fuzzy logic has the lowest overshoot • MPC–fuzzy–PID in a series configuration balances speed and robustness • Hybrid control strategies effectively combine responsiveness and adaptability • No single control approach outperforms the others across all metrics