Enhancing the Output Characteristics of a Photovoltaic Position Sensor Using a Feed-Forward Neural Network

Abstract:

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Tracking solar-power devices often employ photovoltaic position sensors to detect the angle of misalignment between the axis of mounted solar panels and that of sunlight. The nonlinear input-output characteristics of this type of sensors tend to complicate controller design in such systems. This paper presents a nonlinear mathematical model of the photovoltaic position sensor. A three-layer feedforward neural network was trained to linearise the characteristics of the sensor. The MATLAB neural network tool (nntool) was used for neural network training. A final error of was obtained after training. Simulation of the neural network showed that linear sensor characteristics could be reproduced throughout the domain of sensor operation.

Info:

Periodical:

Advanced Materials Research (Volumes 62-64)

Edited by:

Prof. A.O. Akii Ibhadode, A.I. Igbafe and B.U. Anyata

Pages:

506-511

DOI:

10.4028/www.scientific.net/AMR.62-64.506

Citation:

J. T. Agee et al., "Enhancing the Output Characteristics of a Photovoltaic Position Sensor Using a Feed-Forward Neural Network", Advanced Materials Research, Vols. 62-64, pp. 506-511, 2009

Online since:

February 2009

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Price:

$35.00

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