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In order to enhance the efficiency of the photovoltaic system, a technique called Maximum Power Point Tracking (MPPT) is substantially used. It allows photovoltaic panel operates at its maximum output power. Fuzzy logic technique seems to be an auspicious solution that ensures optimal operation of photovoltaic system. It is a fashionable, flexible...
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... It is applied to the photovoltaic system since it is robust and a favorable method that works without oscillations at the optimal point. The main disadvantages of FLC are the problem of shifting the operating point away from the peak optimum point associated with rapidly changing irradiance of more than 10 W/m 2 /s as demonstrated in figure 8, and complicated implementation compared to traditional MPPT methods [19]. A modified P&O algorithm based FLC methodology was introduced in this work and designed for MPPT to combine the advantages of FLC and P&O MPPT algorithms while reducing their drawbacks. ...
This paper presents the design and implementation of intelligent maximum power point tracking (MPPT) technique for Photovoltaic (PV) systems. The proposed MPPT is based on the fuzzy logic controller (FLC). FLCs have the benefit of being very easy to design as they don't need accurate knowledge of the system and work well for the nonlinear system. The MATLAB/Simulink was used to verify the proposed method, with three scenarios of environment conditions. The DC-DC converter has been designed and simulated using PLECS simulation software, then implemented practically in order to work as impedance matching between PV source and load. The system was built based on Field Programmable Gate Array (FPGA) and connected to the PV panel and tested practically at the site for different environment conditions and compared with measurements obtained using solar analyzer device. According to the simulated and experimental results, the proposed method capable to find the maximum power point (MPP) under different climate conditions excellently with compared to perturb and observation (P&O) method. Also, it has very low oscillation about (MPP) and high response, as a result, efficiency is enhanced, providing maximum power transfer to load.
... The algorithm is then compared with particle swarm optimization one [4]. The most widely used AI algorithm for MPPT is fuzzy logic one, due to its simplicity, flexibility, and robustness [5]. FPGAs have many advantages over other hardware implementations: ...
In this paper a reconfigurable FPGA implementation for the maximum power point tracking (MPPT) in photovoltaic systems (PV) is presented. The proposed MPPT controller is based on fuzzy logic and operates under variable irradiance and temperature conditions. The fuzzy controller is developed at first using matlab Simulink model. It includes the PV panel, boost converter and MPPT controller. The tested controller is implemented in VHDL. The pro- posed design has the advantage of high flexibility and re-configurability, while maintaining faster response than other hardware implementations. The design has also the advantage of low cost and power consumption. To validate the design, simulation comparison between the Matlab Simulink and VHDL results are provided. The VHDL controller is implemented and synthesized on Spartan 6 field programmable gate arrays FPGA. A graphical user interface GUI is implemented to help the system designer reconfigure the fuzzy controller.
Este artículo presenta la aplicación de las técnicas para la sincronización local de un sistema de manufactura didáctico compuesto por actuadores, robots y una banda síncrona. Las técnicas utilizadas fueron: 1) El método del vórtice, 2) Método de modularización, 3) Método de distribución de sensado y 4) Método de distribución de tiempos. Para lograr realizar la sincronización local o también llamada modular, se partió del conocimiento de una distribución de planta y de una crónica de procesos, así como de un volumen de producción fijo y de tiempos de proceso fijos; posteriormente se distribuyeron sensores a lo largo del recorrido de ida del sistema productivo. El sistema fue partido o modularizado sistemáticamente en dos módulos de producción bajo el concepto de la terna mínima sincronizable. Se aplicó el método del vórtice el cual consiste en una figura cuyos arcos conectan máquinas sucesoras y antecesoras en torno a la máquina principal formando grupos de máquinas. Se propone un diseño de rutas de trabajo de cada máquina a las cuales se les distribuyen en forma sistemática los tiempos de proceso. Todo el proceso de análisis se concentra en tablas de sincronización local, las cuales indica los tiempos de ciclo de cada máquina, los tipos de ciclos y los sensores involucrados. Adicionalmente, se incluye una simulación en FluidSim de los módulos de producción. Los resultados obtenidos producto de la sincronización local se utilizan para diversas aplicaciones, entre ellas para el control de procesos y la sincronización global.
