DocumentCode
3327730
Title
Nonlinear Modeling of MEMS Deformable Mirror Based on Neural Network
Author
Li, Jie ; Wu, Peng
Author_Institution
Dept. of Electr. & Inf. Eng., Wuhan Polytech. Univ., Wuhan, China
fYear
2011
fDate
16-18 May 2011
Firstpage
1
Lastpage
4
Abstract
The nonlinear response and strong coupling effect of control channel in Deformable Mirrors make it difficult to obtain the desired mirror surface shapes. An efficient nonlinear model of deformation with respect to input voltages is presented using a back propagation neural network (BPNN). The residual relative error of the proposed model shows the improvement of accuracy of an order about 5 as compared to that of linear model, and with no significant increase of time.
Keywords
backpropagation; micro-optomechanical devices; mirrors; neural nets; optical engineering computing; MEMS deformable mirror; backpropagation neural network; deformation; mirror surface shapes; nonlinear modeling; strong coupling effect; Actuators; Adaptation model; Deformable models; Laser modes; Mathematical model; Mirrors; Shape;
fLanguage
English
Publisher
ieee
Conference_Titel
Photonics and Optoelectronics (SOPO), 2011 Symposium on
Conference_Location
Wuhan
ISSN
2156-8464
Print_ISBN
978-1-4244-6555-2
Type
conf
DOI
10.1109/SOPO.2011.5780582
Filename
5780582
Link To Document