Adaptive Wavelet Neural Network Control With Hysteresis Estimation for Piezo-Positioning Mechanism

2006 ◽  
Vol 17 (2) ◽  
pp. 432-444 ◽  
Author(s):  
F.-J. Lin ◽  
H.-J. Shieh ◽  
P.-K. Huang
2015 ◽  
Vol 39 (3) ◽  
pp. 625-635
Author(s):  
Yung-Lung Lee ◽  
Shou-Jen Hsu ◽  
Yen-Bin Chen

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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