Hopfield Neural Network Optimized Fuzzy Logic Controller for Maximum Power Point Tracking in a Photovoltaic System

<table class="table-group" width="800px"><tr class="fig-image" id="a"><td><img alt="798361.fig.001a" src="https://static.hindawi.com/articles/ijp/volume-2012/798361/figures/798361.fig.001a.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(a) </b>Effect of irradiation</td></tr></table></td></tr><tr class="fig-image" id="b"><td><img alt="798361.fig.001b" src="https://static.hindawi.com/articles/ijp/volume-2012/798361/figures/798361.fig.001b.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(b) </b>Effect of temperature</td></tr></table></td></tr></table>

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</svg> Characteristic of a typical PV module.</table>

International Journal of Photoenergy

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Figure 1

Figure 1: Hopfield Neural Network Optimized Fuzzy Logic Controller for Maximum Power Point Tracking in a Photovoltaic System 