Intelligent Control, Filtering and Model Reduction Analysis for Fuzzy-Model-Based Systems

2022 ◽  
Author(s):  
Xiaojie Su ◽  
Yao Wen ◽  
Yue Yang ◽  
Peng Shi
2011 ◽  
Vol 486 ◽  
pp. 262-265
Author(s):  
Amit Kohli ◽  
Mudit Sood ◽  
Anhad Singh Chawla

The objective of the present work is to simulate surface roughness in Computer Numerical Controlled (CNC) machine by Fuzzy Modeling of AISI 1045 Steel. To develop the fuzzy model; cutting depth, feed rate and speed are taken as input process parameters. The predicted results are compared with reliable set of experimental data for the validation of fuzzy model. Based upon reliable set of experimental data by Response Surface Methodology twenty fuzzy controlled rules using triangular membership function are constructed. By intelligent model based design and control of CNC process parameters, we can enhance the product quality, decrease the product cost and maintain the competitive position of steel.


2004 ◽  
Vol 44 (6) ◽  
pp. 1108-1113 ◽  
Author(s):  
M.-Y. Chen ◽  
D. A. Linkens ◽  
D. J. Howarth ◽  
J. H. Beynon

2021 ◽  
Vol 4 ◽  
pp. 100098
Author(s):  
Rodrigo Sislian ◽  
Flávio V. da Silva ◽  
Marco A. Coghi ◽  
Rubens Gedraite

Author(s):  
Chengcheng Lu ◽  
Zheng Lv ◽  
Linqing Wang ◽  
Jun Zhao ◽  
Wei Wang

2009 ◽  
Vol 26 (7) ◽  
pp. 745-760 ◽  
Author(s):  
Meng‐Lung Lin ◽  
Cheng‐Wu Chen ◽  
Qiu‐Bing Wang ◽  
Yu Cao ◽  
Jyh‐Yi Shih ◽  
...  

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