Journal of
Systemics, Cybernetics and Informatics
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ISSN: 1690-4524 (Online)


Peer Reviewed Journal via three different mandatory reviewing processes, since 2006, and, from September 2020, a fourth mandatory peer-editing has been added.

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Honorary Editorial Advisory Board's Chair
William Lesso (1931-2015)

Editor-in-Chief
Nagib C. Callaos


Sponsored by
The International Institute of
Informatics and Systemics

www.iiis.org
 

Editorial Advisory Board

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Editors

Journal's Reviewers
Call for Special Articles
 

Description and Aims

Submission of Articles

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Information to Contributors

Editorial Peer Review Methodology

Integrating Reviewing Processes


Philosophy and Cybernetics: Questions and Issues
Thomas Marlowe, Fr. Joseph R. Laracy
(pages: 1-23)

Reconceiving Cybernetics in Light of Thomistic Realism
John T. Laracy, Fr. Joseph R. Laracy
(pages: 24-39)

Nascent Cybernetics, Humanism, and Some Scientistic Challenges
Zachary M. Mabee
(pages: 40-52)

Kant, Cybernetics, and Cybersecurity: Integration and Secure Computation
Jon K. Burmeister, Ziyuan Meng
(pages: 53-78)

Interplay Between Cybernetics and Philosophy as an Essential Condition for Learning
Maria Jakubik
(pages: 79-97)

Towards a General Theory of Change: A Cybernetic and Philosophical Understanding
Gianfranco Minati
(pages: 98-109)

Artificial Intelligence and Human Intellect
Víctor Velarde-Mayol
(pages: 110-127)

The Philosophy of Cybernetics
Jeremy Horne
(pages: 128-159)

Cybernetics and Philosophy in a Translation of Oedipus the King and Its Performance
Ekaterini Nikolarea
(pages: 160-190)

Linguistic Philosophy of Cyberspace
Rusudan Makhachashvili, Ivan Semenist
(pages: 191-207)

Systems Philosophy and Cybernetics
Nagib Callaos
(pages: 208-284)


 

Abstracts

 


ABSTRACT


Maximum Power Point Tracking Method Based on Perturb and Observe Coupled with a Neural Network for Photovoltaic Systems Operating Under Fast Changing Environments

Yesid Briceno-Fajardo, Gustavo Cerda-Villafana, Sergio Ledesma-Orozco


The output power of Photovoltaic (PV) arrays presents a nonlinear behavior. Its maximum power point varies with the cell’s temperature and solar radiation. It is due to this situation that Maximum Power Point Tracking (MPPT) methods have been proposed and used in order to maximize the PV array output power. This paper presents an artificial neural network (ANN) combined with the classic Perturbation and Observation (P&O) algorithm to accelerate the search of such Maximum Power Point. Simulations generated using Matlab/Simulink show the improvement compared to the P&O alone and the hardware implementation, using a 16-bit microcontroller corroborates these findings.

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