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Energies 2017, 10(3), 394;

Neuro-Fuzzy Wavelet Based Adaptive MPPT Algorithm for Photovoltaic Systems

State Key Laboratory of Power Transmission Equipment and System Security and New Technology, School of Electrical Engineering, Chongqing University, Chongqing 400044, China
Department of Electrical and Electronics Engineering, Faculty of Engineering, Sakarya University, Serdivan/Sakarya 54050, Turkey
Department of Electrical Engineering, COMSATS Institute of Information Technology, Abbottabad 22060, Pakistan
Author to whom correspondence should be addressed.
Academic Editor: Ying-Yi Hong
Received: 2 February 2017 / Revised: 6 March 2017 / Accepted: 10 March 2017 / Published: 20 March 2017
(This article belongs to the Special Issue Electric Power Systems Research 2017)
Full-Text   |   PDF [5202 KB, uploaded 20 March 2017]   |  


An intelligent control of photovoltaics is necessary to ensure fast response and high efficiency under different weather conditions. This is often arduous to accomplish using traditional linear controllers, as photovoltaic systems are nonlinear and contain several uncertainties. Based on the analysis of the existing literature of Maximum Power Point Tracking (MPPT) techniques, a high performance neuro-fuzzy indirect wavelet-based adaptive MPPT control is developed in this work. The proposed controller combines the reasoning capability of fuzzy logic, the learning capability of neural networks and the localization properties of wavelets. In the proposed system, the Hermite Wavelet-embedded Neural Fuzzy (HWNF)-based gradient estimator is adopted to estimate the gradient term and makes the controller indirect. The performance of the proposed controller is compared with different conventional and intelligent MPPT control techniques. MATLAB results show the superiority over other existing techniques in terms of fast response, power quality and efficiency. View Full-Text
Keywords: photovoltaic systems; maximum power point tracking; adaptive control; wavelets photovoltaic systems; maximum power point tracking; adaptive control; wavelets

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Hassan, S.Z.; Li, H.; Kamal, T.; Arifoğlu, U.; Mumtaz, S.; Khan, L. Neuro-Fuzzy Wavelet Based Adaptive MPPT Algorithm for Photovoltaic Systems. Energies 2017, 10, 394.

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