Adaptive Fuzzy-Neural-Network Design for Voltage Tracking Control of a DC–DC Boost Converter

2012 ◽  
Vol 27 (4) ◽  
pp. 2104-2115 ◽  
Author(s):  
Rong-Jong Wai ◽  
Li-Chung Shih
Author(s):  
Waleed Ishaq Hameed ◽  
Baha Aldeen Sawadi ◽  
Ali Muayed

<span lang="EN-US">This paper deals with voltage tracking control of DC- DC boost converter based on Fuzzy neural network. Maintaining the output voltage of the boost converter in some applications are very important, especially for sudden change in the load or disturbance in the input voltage. Traditional control methods usually have some disadvantages in eliminating these disturbances, as the speed of response to these changes is slow and thus affect the regularity of the output voltage of the converter. The strategy is to sense the output voltage across the load and compare it with the reference voltage to ensure that it follows the required reference voltages. In this research, fuzzy neural was introduced to achieve the purpose of voltage tracking by training the parameter of controller based on previous data. These data sets are the sensing input voltage of the converter and the value of the output load changes. To establish the performance of proposed method, MATLAB/SIMULINK environments are presented, simulation results shows that proposed method works more precisely, faster in response and elimination the disturbances</span>


2021 ◽  

Abstract The full text of this preprint has been withdrawn by the authors due to author disagreement with the posting of the preprint. Therefore, the authors do not wish this work to be cited as a reference. Questions should be directed to the corresponding author.


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