DocumentCode :
728426
Title :
Process modeling and advanced control methods for Exposure Controlled Projection Lithography
Author :
Xiayun Zhao ; Rosen, David W.
Author_Institution :
George W. Woodruff Sch. of Mech. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
fYear :
2015
fDate :
1-3 July 2015
Firstpage :
3643
Lastpage :
3648
Abstract :
The Exposure Controlled Projection Lithography (ECPL) is a photopolymerization-based additive manufacturing process, which cures a 3D part by projecting patterned UV light from beneath a stationary and transparent resin chamber. Its application in microfabrication is limited by the current open-loop process control method. The overall research goal is to develop some closed-loop control system for the black / grey box ECPL process. In this paper, we presented two process modeling and control systems for ECPL - a lumped parameters model with an Kalman filter equipped Evolutionary Cycle to Cycle (EC2C) control scheme, and a novel backstepping dynamics model with Adaptive Neural Network Backstepping (ANNB) control method. EC2C and ANNB methods adopt different process models, control approaches and algorithms, and can be applied under different development stages and application scenarios of the ECPL process. Preliminary study concluded that the EC2C and ANNB control methods are capable of tracking the process dynamics, thus are promising to be able to improve the ECPL process precision and robustness.
Keywords :
Kalman filters; adaptive control; control nonlinearities; lumped parameter networks; micro-optics; microfabrication; neurocontrollers; optical polymers; photolithography; polymerisation; process control; resins; ANNB control method; EC2C control method; Kalman filter; adaptive neural network backstepping; backstepping dynamics model; black box ECPL process; current open loop process control method; evolutionary cycle to cycle; exposure controlled projection lithography; grey box ECPL process; lumped parameter model; microfabrication; patterned UV light projection; photopolymerization-based additive manufacturing process; stationary resin chamber; transparent resin chamber; Adaptation models; Kalman filters; Mathematical model; Noise; Noise measurement; Process control; Semiconductor process modeling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference (ACC), 2015
Conference_Location :
Chicago, IL
Print_ISBN :
978-1-4799-8685-9
Type :
conf
DOI :
10.1109/ACC.2015.7171896
Filename :
7171896
Link To Document :
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