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Journal ArticleDOI

FPGA-based implementation of a fuzzy controller (MPPT) for photovoltaic module

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TLDR
The hardware implementation of a two-inputs one-output digital Fuzzy Logic Controller on a Xilinx reconfigurable Field-Programmable Gate Array (FPGA) using VHDL Hardware Description Language shows a satisfactory performance with a good agreement between the expected and the obtained values.
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This article is published in Energy Conversion and Management.The article was published on 2011-07-01. It has received 103 citations till now. The article focuses on the topics: ModelSim & Field-programmable gate array.

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Citations
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Journal ArticleDOI

Classification and comparison of maximum power point tracking techniques for photovoltaic system: A review

TL;DR: In this paper, a classification scheme for MPPT methods based on three categories: offline, online and hybrid methods is introduced, which can provide a convenient reference for future work in PV power generation, is based on the manner in which the control signal is generated and the PV power system behavior as it approaches steady state conditions.
Journal ArticleDOI

Applications of fuzzy logic in renewable energy systems – A review

TL;DR: An attempt has been made to review the applications of fuzzy logic based models in renewable energy systems namely solar, wind, bio-energy, micro-grid and hybrid applications and indicates that fuzzy based models provide realistic estimates.
Journal ArticleDOI

Adaptive fuzzy controller based MPPT for photovoltaic systems

TL;DR: In this article, an intelligent approach to optimize the performances of photovoltaic systems is presented, which consists of a PV panel, a DC-DC boost converter, a maximum power point tracker controller and resistive load.
Journal ArticleDOI

A novel beta parameter based fuzzy-logic controller for photovoltaic MPPT application

TL;DR: A novel beta parameter three-input one-output fuzzy-logic based maximum power point tracking (MPPT) algorithm is presented for the photovoltaic (PV) system application by introducing a third input: an intermediate variable β.
Journal ArticleDOI

The role of artificial intelligence in photo-voltaic systems design and control: A review

TL;DR: In this article, a review on the up-to-date scientific achievements in applying Artificial Intelligence (AI) techniques in Photovoltaic (PV) systems is presented, which surveys the role of AI algorithms in modeling, sizing, control, fault diagnosis and output estimation of PV systems.
References
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Journal ArticleDOI

Review of the maximum power point tracking algorithms for stand-alone photovoltaic systems

TL;DR: All algorithms, direct and indirect, can be included in some of the DC/DC converters, Maximum power point trackings (MPPTs), for the stand-alone systems and in this article they are grouped as either direct or nondirect methods.
Journal ArticleDOI

Artificial intelligence techniques for photovoltaic applications: A review

TL;DR: The paper outlines an understanding of how AI systems operate by way of presenting a number of problems in photovoltaic systems application, mainly because of their symbolic reasoning, flexibility and explanation capabilities.
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A novel maximum power fuzzy logic controller for photovoltaic solar energy systems

TL;DR: In this paper, a simple on-line fuzzy logic-based dynamic search, detection and tracking controller is developed to ensure maximum power point (MPP) operation under excursions in solar insolation, ambient temperature and electric load variations.
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An implementation of fuzzy logic controller on the reconfigurable FPGA system

TL;DR: This paper concerns an implementation of a fuzzy logic controller (FLC) on a reconfigurable field-programmable gate array (FPGA) system, and each module is implemented individually on the FLC automatic design and implementation system, which is an integrated development environment for performing many subtasks.
Journal ArticleDOI

FPGA-based real time implementation of MPPT-controller for photovoltaic systems

TL;DR: In this paper, an FPGA-based implementation of a real-time perturb and observe (P&O) algorithm for tracking the maximum power point (MPP) of a photovoltaic (PV) generator is presented.
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