Design of neural network
            <scp>fractional‐order</scp>
            backstepping controller for
            <scp>MPPT</scp>
            of
            <scp>PV</scp>
            systems using
            <scp>fractional‐order</scp>
            boost converter

Youcef, Djourni; Khettab, Khatir; Bensafia, Yassine

doi:10.1002/2050-7038.13188

Cited by 4 publications

(1 citation statement)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The self-adjusting behavior of FOPID control gives it extra performance in order to improve the perturbation rejection aptitude of a PV system in contradiction to uncertain parameters and inputs [66]. Youcef et al [67] suggest a stand-alone PV system operated with a new adaptive (A-FOPID) controller based on the self-adjusting of its parameters to gain the maximum power under changes in the ambient climate. A feed-forward neural network is applied to generate the appropriate voltage signal.…”

Section: Introductionmentioning

confidence: 99%

Enhanced MPPT-Based Fractional-Order PID for PV Systems Using Aquila Optimizer

Tadj,

Chaib,

Choucha

et al. 2023

MCA

View full text Add to dashboard Cite

This paper proposes a controller to track the maximum power point (MPP) of a photovoltaic (PV) system using a fractional-order proportional integral derivative (FOPID) controller. The employed MPPT is operated based on a dp/dv feedback approach. The designed FOPID-MPPT method includes a differentiator of order (μ) and integrator of order (λ), meaning it is an extension of the conventional PID controller. FOPID has more flexibility and achieves dynamical tuning, which leads to an efficient control system. The contribution of our paper lies is optimizing FOPID-MPPT parameters using Aquila optimizer (AO). The obtained results with the proposed AO-based FOPID-MPPT are contrasted with those acquired with moth flame optimizer (MFO). The performance of our FOPID-MPPT controller with the conventional technique perturb and observe (P&O) and the classical PID controller is analyzed. In addition, a robustness test is used to assess the performance of the FOPID-MPPT controller under load variations, providing valuable insights into its practical applicability and robustness. The simulation results clearly prove the superiority and high performance of the proposed control system to track the MPP of PV systems.

show abstract

Section: Introductionmentioning

confidence: 99%