The system's ability to adapt and self-organize are two key factors when it comes to how well the system can survive the changes to the environment and the plant they work within. Intelligent control improves these two factors in controllers. Considering the increasing complexity of dynamic systems along with their need for feedback controls, using more complicated controls has become necessary and intelligent control can be a suitable response to this necessity. This paper briefly describes the structure of intelligent control and provides a review on fuzzy logic and neural networks which are some of the base methods for intelligent control. The different aspects of these two methods are then compared together and an example of a combined method is presented.
| Published in |
Journal of Electrical and Electronic Engineering (Volume 3, Issue 2-1)
This article belongs to the Special Issue Research and Practices in Electrical and Electronic Engineering in Developing Countries |
| DOI | 10.11648/j.jeee.s.2015030201.23 |
| Page(s) | 58-61 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2024. Published by Science Publishing Group |
Intelligent control, Neural networks, Fuzzy logic, Neuro-fuzzy
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| [2] | A. Abraham. “Neuro fuzzy systems: state-of-the-art modeling techniques, connectionist models of neurons,” LNCS, vol. 2084, pp. 269-276, Jun 2001 |
| [3] | C. J. Harris, C. G. Moore, and M. Brown. “Intelligent control: aspects of fuzzy logic and neural network,” World Scientific Series in Robotics and Automated Systems. UK, vol. 6, 1993. |
| [4] | B. Bavarian. “Introduction to neural networks for intelligent control,ˮ IEEE Control System Magazine, California, vol. 8, pp. 3-7, April 1988. |
| [5] | C. C. Lee. “Fuzzy logic in control systems: fuzzy logic controller- part I,ˮ IEEE. Trans. Syst. Man. Cyber. Syst. California, vol. 20, pp. 404-418, Mar/Apr 1990. |
APA Style
Fatemeh Zahedi, Zahra Zahedi. (2015). A Review of Neuro-Fuzzy Systems Based on Intelligent Control. Journal of Electrical and Electronic Engineering, 3(2-1), 58-61. https://doi.org/10.11648/j.jeee.s.2015030201.23
ACS Style
Fatemeh Zahedi; Zahra Zahedi. A Review of Neuro-Fuzzy Systems Based on Intelligent Control. J. Electr. Electron. Eng. 2015, 3(2-1), 58-61. doi: 10.11648/j.jeee.s.2015030201.23
AMA Style
Fatemeh Zahedi, Zahra Zahedi. A Review of Neuro-Fuzzy Systems Based on Intelligent Control. J Electr Electron Eng. 2015;3(2-1):58-61. doi: 10.11648/j.jeee.s.2015030201.23
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Download@article{10.11648/j.jeee.s.2015030201.23,
author = {Fatemeh Zahedi and Zahra Zahedi},
title = {A Review of Neuro-Fuzzy Systems Based on Intelligent Control},
journal = {Journal of Electrical and Electronic Engineering},
volume = {3},
number = {2-1},
pages = {58-61},
doi = {10.11648/j.jeee.s.2015030201.23},
url = {https://doi.org/10.11648/j.jeee.s.2015030201.23},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jeee.s.2015030201.23},
abstract = {The system's ability to adapt and self-organize are two key factors when it comes to how well the system can survive the changes to the environment and the plant they work within. Intelligent control improves these two factors in controllers. Considering the increasing complexity of dynamic systems along with their need for feedback controls, using more complicated controls has become necessary and intelligent control can be a suitable response to this necessity. This paper briefly describes the structure of intelligent control and provides a review on fuzzy logic and neural networks which are some of the base methods for intelligent control. The different aspects of these two methods are then compared together and an example of a combined method is presented.},
year = {2015}
}
TY - JOUR T1 - A Review of Neuro-Fuzzy Systems Based on Intelligent Control AU - Fatemeh Zahedi AU - Zahra Zahedi Y1 - 2015/01/23 PY - 2015 N1 - https://doi.org/10.11648/j.jeee.s.2015030201.23 DO - 10.11648/j.jeee.s.2015030201.23 T2 - Journal of Electrical and Electronic Engineering JF - Journal of Electrical and Electronic Engineering JO - Journal of Electrical and Electronic Engineering SP - 58 EP - 61 PB - Science Publishing Group SN - 2329-1605 UR - https://doi.org/10.11648/j.jeee.s.2015030201.23 AB - The system's ability to adapt and self-organize are two key factors when it comes to how well the system can survive the changes to the environment and the plant they work within. Intelligent control improves these two factors in controllers. Considering the increasing complexity of dynamic systems along with their need for feedback controls, using more complicated controls has become necessary and intelligent control can be a suitable response to this necessity. This paper briefly describes the structure of intelligent control and provides a review on fuzzy logic and neural networks which are some of the base methods for intelligent control. The different aspects of these two methods are then compared together and an example of a combined method is presented. VL - 3 IS - 2-1 ER -
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