DocumentCode
1875435
Title
MIMO stochastic minimum variance control strategies for improving plasma characteristics in Reactive Ion Etching
Author
Tudoroiu, N. ; Khorasani, K. ; Patel, R.V. ; Chiru, C. ; Tudoroiu, Roxana-Elena
fYear
2009
fDate
26-28 Aug. 2009
Firstpage
311
Lastpage
316
Abstract
In this paper, we propose to use multi input multi-output (MIMO) stochastic minimum variance control strategy to control the plasma characteristics in reactive ion etching (RIE) process. Given the RIE model in the state-space representation a stochastic adaptive minimum variance tracking controller (SMVAC) is designed and tuned to control the key plasma parameters. For the stochastic adaptive minimum variance approach a system identification scheme based on the minimum variance principle is integrated with a control strategy derived from minimization of a per-interval performance index. This control strategy performs very well, has good accuracy, as demonstrated in simulation environment, and can easily be applied to MIMO RIE system. The principal idea is that by controlling appropriate key plasma parameters (the concentrations of the reactive radicals and ions and ions energy) it is possible to improve the etch performance of the reactive ion etchers, namely their selectivity, uniformity, anisotropy and etch depth. The proposed real-time control strategies reveal superior accuracy and performance when compared to the results available in the plasma literature.
Keywords
MIMO systems; minimisation; sputter etching; stochastic processes; MIMO; minimum variance principle; multiinput multioutput system; plasma characteristic; reactive ion etching; state-space representation; stochastic adaptive minimum variance tracking controller; Adaptive control; Etching; MIMO; Plasma applications; Plasma properties; Plasma simulation; Programmable control; Stochastic processes; Stochastic systems; System identification; Feedback control; MIMO and SISO control systems; RIE process; stochastic adaptive minimum variance control (SMVAC); system identification;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Signal Processing, 2009. WISP 2009. IEEE International Symposium on
Conference_Location
Budapest
Print_ISBN
978-1-4244-5057-2
Electronic_ISBN
978-1-4244-5059-6
Type
conf
DOI
10.1109/WISP.2009.5286547
Filename
5286547
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