Paper Title:
Enhancing the Output Characteristics of a Photovoltaic Position Sensor Using a Feed-Forward Neural Network
  Abstract

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
A.O. Akii Ibhadode, I.A. Igbafe and B.U. Anyata
Pages
506-511
DOI
10.4028/www.scientific.net/AMR.62-64.506
Citation
J. T. Agee, S. Masupe, M. Jeffrey, A. A. Jimoh, "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
$32.00
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