Selection of GTAW process parameter and optimizing the weld pool geometry for AA 7075-T6 Aluminium alloy

2018 ◽  
Vol 5 (11) ◽  
pp. 25045-25055 ◽  
Author(s):  
K.S. Pujari ◽  
D.V. Patil ◽  
Gurunath Mewundi
Keyword(s):  
Aluminium Alloy ◽  
Weld Pool ◽  
Process Parameter ◽  
Gtaw Process ◽  
Weld Pool Geometry ◽  
Aa 7075 ◽  
Selection Of

scholarly journals AHP and TOPSIS based selection of aluminium alloy for automobile panels

2019 ◽  
Vol 3 (1) ◽  
pp. 43-50
Author(s):  
D. Swapna ◽  
Ch. Srinivasa Rao ◽  
D. Sameer Kumar ◽  
S. Radhika
Keyword(s):  
Aluminium Alloy ◽  
Selection Of

Simple constitutive analysis of AA 7075-T6 aluminium alloy deformed at low deformation temperatures

2012 ◽  
Vol 28 (6) ◽  
pp. 668-679
Author(s):  
E S Puchi-Cabrera ◽  
M H Staia ◽  
E Ochoa-Pérez ◽  
J G La Barbera-Sosa ◽  
Y Y Santana ◽  
...  
Keyword(s):  
Aluminium Alloy ◽  
Constitutive Analysis ◽  
Aa 7075

Fuzzy-based Gain Adaptive Scheme for Set-Point Modulated Model Reference Adaptive Controller

2018 ◽  
Vol 7 (4) ◽  
pp. 1-19
Author(s):  
A. K. Pal ◽  
Indrajıt Naskar ◽  
Sampa Paul
Keyword(s):  
Adaptive Controller ◽  
Process Parameter ◽  
System Stability ◽  
Modulation Scheme ◽  
Model Reference ◽  
Set Point ◽  
Automatic Selection ◽  
Parameter Variations ◽  
Model Reference Adaptive ◽  
Selection Of

In model reference adaptive controller (MRACs), the adaptive gain of the controller is varied according to the process dynamic variation as it is directly related with the system stability. In MRAC, there is no provision of an automatic selection of adaptive gain and adaptation rate. To get rid of this problem and for the automatic selection of adaptive gain, a fuzzy-based scheme is presented in this article. In the proposed fuzzy-based technique, the controller output gain is illustrated as the function of input process parameters, which is continuously amended for any process parameter variations. A set-point modulation scheme is also incorporated to tackle the undesired process parameter variations and to improve performance indices of the process under control. The performance of the proposed set-point modulated fuzzy-based model reference adaptive controller (SFMRAC) is demonstrated on different second order linear, marginally stable and nonlinear models. The scheme is also explored on a real-time twin arm overhead crane for transport of material without pendulation.

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