A maximum power point tracker for photovoltaic energy systems based on fuzzy neural networks
Author:
Publisher
Zhejiang University Press
Subject
General Engineering
Link
http://link.springer.com/content/pdf/10.1631/jzus.A0820128.pdf
Reference20 articles.
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2. Brambilla, A., 1999. New Approach to Photovoltaic Arrays Maximum Power Point Tracking. 30th Annual IEEE Power Electronics Specialists Conf., South Carolina, USA, p.632–637.
3. Das, D., Esmaili, R., Xu, L., Nichols, D., 2005. An Optimal Design of a Grid Connected Hybrid Wind/Photovoltaic/Fuel Cell System for Distributed Energy Production. 32nd Annual Conf. of the IEEE Industrial Electronics Society, Paris, France, p.2499–2504.
4. Hiyama, T., Kouzuma, S., Imakubo, T., Ortmeyer, T.H., 1995. Evaluation of neural network based real time maximum power tracking controller for PV system. IEEE Trans. Energy Conv., 10(3):543–548. [doi:10.1109/60.464880]
5. Huang, S.J., Huang, K.S., Chiou, K.C., 2003. Development and application of a novel radial basis function sliding mode controller. Mechatronics, 13(4):313–329. [doi:10. 1016/S0957-4158(01)00050-2]
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