DocumentCode :
1699688
Title :
Multivariate statistical model between stressed-lap surface deformation and driving forces
Author :
Xie, Kaigui ; Ouyang, Wen ; Yuan, Jiahu ; Wan, Yongjian ; Fan, Bing
Author_Institution :
Dept. of Power Syst., Chongqing Univ., Chongqing
fYear :
2008
Firstpage :
1
Lastpage :
4
Abstract :
Regression analysis is used to analysis the changing rule between stressed-lap surface deformation and driving forces. And the multivariate regression model of stressed-lap surface deformation about driving forces is proposed. In the model, surface deformation is dependent variable, driving forces are argument. And the regression coefficients are solved by least-squares procedure. Thereby, the surface deformation could be calculated quickly for random driving forces. Moreover, the multivariate regression model between driving forces and stressed-lap surface deformation is also proposed in this paper. This two model processes are similar. The driving forces are quickly calculated for random surface deformation through last model. The multivariate regression model between driving forces and surface deformation is proposed for a 420 mm diameter stressed-lap with 12 motors and 60 macro-movement sensors. The result is very close to theoretical value and indicates accuracy and feasibility of model.
Keywords :
least squares approximations; multivariable control systems; optical fabrication; polishing; regression analysis; driving forces; least-squares procedure; multivariate statistical model; regression analysis; stressed-lap surface deformation; Deformable models; Electric variables control; Frequency; Intelligent control; Multivariate regression; Neural networks; Optical computing; Optical variables control; Power system modeling; Stress control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automation Congress, 2008. WAC 2008. World
Conference_Location :
Hawaii, HI
Print_ISBN :
978-1-889335-38-4
Electronic_ISBN :
978-1-889335-37-7
Type :
conf
Filename :
4699175
Link To Document :
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