scholarly journals Wavelet–Neural–Network Control for Maximization of Energy Capture in Grid Connected Variable Speed Wind Driven Self- Excited Induction Generator System

10.5772/51253 ◽  
2013 ◽  
Author(s):  
Fayez F. M. El-Sousy ◽  
Awad Kh.
Keyword(s):  
Neural Network ◽  
Wavelet Neural Network ◽  
Network Control ◽  
Induction Generator ◽  
Neural Network Control ◽  
Variable Speed ◽  
Generator System ◽  
Energy Capture

STUDY ON THE DESIGN ADAPTIVE RECURRENT WAVELET NEURAL NETWORK CONTROL OF AN AUTO TIG WELD SYSTEM

2015 ◽  
Vol 39 (3) ◽  
pp. 625-635
Author(s):  
Yung-Lung Lee ◽  
Shou-Jen Hsu ◽  
Yen-Bin Chen
Keyword(s):  
Neural Network ◽  
Welding Current ◽  
Wavelet Neural Network ◽  
Network Control ◽  
Neural Network Control ◽  
Argon Flow Rate ◽  
Argon Flow ◽  
Human Operators ◽  
And Performance ◽  
Wire Feed

An adaptive recurrent wavelet neural network control (WNN) method was developed to improve quality and system performance in welded aluminum alloy vacuum chamber production. Tests were carried out using a multi-gun automatic system. Using WNN, this research is meant to overcome weld inconsistencies and faults that cause leaks and are due to variability of skill and performance among human operators. By using this method to control welding current, wire feed rate, argon flow rate and welding speed, desired results are hopefully achieved.

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