Robust Backstepping Super-Twisting MPPT Controller for Photovoltaic Systems Under Dynamic Shading Conditions

Kamran Ali (), Shafaat Ullah () and Eliseo Clementini
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Kamran Ali: Department of Industrial and Information Engineering and Economics, University of L’Aquila, 67100 L’Aquila, AQ, Italy
Shafaat Ullah: Department of Electrical Engineering, University of Engineering and Technology Peshawar, Bannu Campus, Bannu 28100, Pakistan
Eliseo Clementini: Department of Industrial and Information Engineering and Economics, University of L’Aquila, 67100 L’Aquila, AQ, Italy

Energies, 2025, vol. 18, issue 19, 1-25

Abstract: In this research article, a fast and efficient hybrid Maximum Power Point Tracking (MPPT) control technique is proposed for photovoltaic (PV) systems. The method combines two phases—offline and online—to estimate the appropriate duty cycle for operating the converter at the maximum power point (MPP). In the offline phase, temperature and irradiance inputs are used to compute the real-time reference peak power voltage through an Adaptive Neuro-Fuzzy Inference System (ANFIS). This estimated reference is then utilized in the online phase, where the Robust Backstepping Super-Twisting (RBST) controller treats it as a set-point to generate the control signal and continuously adjust the converter’s duty cycle, driving the PV system to operate near the MPP. The proposed RBST control scheme offers a fast transient response, reduced rise and settling times, low tracking error, enhanced voltage stability, and quick adaptation to changing environmental conditions. The technique is tested in MATLAB/Simulink under three different scenarios: continuous variation in meteorological parameters, sudden step changes, and partial shading. To demonstrate the superiority of the RBST method, its performance is compared with classical backstepping and integral backstepping controllers. The results show that the RBST-based MPPT controller achieves the minimum rise time of 0.018 s , the lowest squared error of 0.3015 V , the minimum steady-state error of 0.29 %, and the highest efficiency of 99.16 %.

Keywords: maximum power point tracking (MPPT); photovoltaic (PV); DC–DC power converter; robust backstepping super twisting; ANFIS; hybrid method; partial shading (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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