Table of Contents Author Guidelines Submit a Manuscript
International Journal of Photoenergy
Volume 2016, Article ID 5214061, 16 pages
http://dx.doi.org/10.1155/2016/5214061
Research Article

Sliding Mode Real-Time Control of Photovoltaic Systems Using Neural Estimators

1Electrical Engineering Department, Faculty of Engineering Vitoria-Gasteiz, University of the Basque Country, Nieves Cano 12, 01006 Vitoria-Gasteiz, Spain
2Systems Engineering and Automatic Control Department, Faculty of Engineering Vitoria-Gasteiz, University of the Basque Country, Nieves Cano 12, 01006 Vitoria-Gasteiz, Spain
3Electrical Engineering Department, Faculty of Engineering, University of the Basque Country, Alameda Urquijo, s/n, 48013 Bilbao, Spain
4Department of Electrical, Electronics and Communications Engineering, American University of Ras Al Khaimah, Sheikh Saqr Bin Khalid Rd., Ras Al Khaimah, UAE

Received 15 April 2016; Revised 13 June 2016; Accepted 28 June 2016

Academic Editor: Prakash Basnyat

Copyright © 2016 J. A. Ramos-Hernanz et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The maximum power point tracking (MPPT) problem has attracted the attention of many researchers, because it is convenient to obtain the maximum power of a photovoltaic module regardless of the weather conditions and the load. In this paper, a novel control for a boost DC/DC converter has been introduced. It is based on a sliding mode controller (SMC) that takes a current signal as reference instead of a voltage, which is generated by a neuronal reference current generator. That reference current indicates the current () at the maximum power point (MPP) for given weather conditions. In order to test the designed control system, a photovoltaic module model based on a second artificial neuronal network (ANN) has been obtained from experimental data gathered during 18 months in the Faculty of Engineering Vitoria-Gasteiz (Spain). We have analyzed the performance of such model and we found that it is very accurate (MSE = 0.062 A and = 0.991 with test dataset). We also have tested the performance of the overall SMC design with both simulated and real tests, concluding that it guarantees that the power in the output of the converter is very close to the power of the photovoltaic module output.