Hopfield Neural Network Optimized Fuzzy Logic Controller for Maximum Power Point Tracking in a Photovoltaic System
Joint Authors
Shareef, Hussain
Subiyanto,
Mohamed, Azah
Source
International Journal of Photoenergy
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2011-10-24
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
This paper presents a Hopfield neural network (HNN) optimized fuzzy logic controller (FLC) for maximum power point tracking in photovoltaic (PV) systems.
In the proposed method, HNN is utilized to automatically tune the FLC membership functions instead of adopting the trial-and-error approach.
As in any fuzzy system, initial tuning parameters are extracted from expert knowledge using an improved model of a PV module under varying solar radiation, temperature, and load conditions.
The linguistic variables for FLC are derived from, traditional perturbation and observation method.
Simulation results showed that the proposed optimized FLC provides fast and accurate tracking of the PV maximum power point under varying operating conditions compared to that of the manually tuned FLC using trial and error.
American Psychological Association (APA)
Subiyanto, & Mohamed, Azah& Shareef, Hussain. 2011. Hopfield Neural Network Optimized Fuzzy Logic Controller for Maximum Power Point Tracking in a Photovoltaic System. International Journal of Photoenergy،Vol. 2012, no. 2012, pp.1-13.
https://search.emarefa.net/detail/BIM-499023
Modern Language Association (MLA)
Subiyanto,…[et al.]. Hopfield Neural Network Optimized Fuzzy Logic Controller for Maximum Power Point Tracking in a Photovoltaic System. International Journal of Photoenergy No. 2012 (2012), pp.1-13.
https://search.emarefa.net/detail/BIM-499023
American Medical Association (AMA)
Subiyanto, & Mohamed, Azah& Shareef, Hussain. Hopfield Neural Network Optimized Fuzzy Logic Controller for Maximum Power Point Tracking in a Photovoltaic System. International Journal of Photoenergy. 2011. Vol. 2012, no. 2012, pp.1-13.
https://search.emarefa.net/detail/BIM-499023
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-499023