2020
DOI: 10.3390/en13143695
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Supertwisting Sliding Mode Algorithm Based Nonlinear MPPT Control for a Solar PV System with Artificial Neural Networks Based Reference Generation

Abstract: The problem of extracting maximum power from a photovoltaic (PV) system with negligible power loss is concerned with the power generating capability of the PV array and nature of the output load. Changing weather conditions and nonlinear behavior of PV systems pose a challenge in tracking of varying maximum power point. A robust nonlinear controller is required to ensure maximum power point tracking (MPPT) by handling nonlinearities of a system and making it robust against changing environmental conditions. Sl… Show more

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Cited by 43 publications
(25 citation statements)
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References 27 publications
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“…In [ 66 ] developed a super twisting sliding mode with ANN algorithm for tracking MPP. They mention that since PVS in changing conditions (T/G) behaves as a nonlinear system, a nonlinear controller is required to ensure MPP.…”
Section: Artificial Neural Network For Mppt Control In Pv Systemsmentioning
confidence: 99%
“…In [ 66 ] developed a super twisting sliding mode with ANN algorithm for tracking MPP. They mention that since PVS in changing conditions (T/G) behaves as a nonlinear system, a nonlinear controller is required to ensure MPP.…”
Section: Artificial Neural Network For Mppt Control In Pv Systemsmentioning
confidence: 99%
“…The results explain good performance of ANN-FLC as compared to traditional incremental conductance (IC). In [24], authors have investigated the method to achieve acceptable tracking time and less power oscillation by adjusting the changing step size of Flyback inverter. Solar irradiance is adopted as an input of ANN which is used to appropriate modulation step size.…”
Section: Related Workmentioning
confidence: 99%
“…Performance mainly depends on human expertise. -Non-linear: sliding mode [20] and backstepping [21]. Good performance in terms of robustness and stability.…”
Section: Introductionmentioning
confidence: 99%
“…Performance depends on initial conditions and design parameters. ‐Artificial intelligence: fuzzy logic (FL) [18] and neural networks (NN) [19]. Performance mainly depends on human expertise. ‐Non‐linear: sliding mode [20] and backstepping [21]. Good performance in terms of robustness and stability.…”
Section: Introductionmentioning
confidence: 99%