Indirect adaptive control of reactive ion etching using neural networks.

Indirect adaptive control of reactive ion etching using neural networks.

This paper explores the use of neural networks for real-time, model-based feedback control of reactive ion etching (RIE). This objective is accomplished in part by constructing a predictive model for the system which can be approximately inverted to achieve the desired control. An indirect adaptive...

Ausführliche Beschreibung

Bibliographische Detailangaben
Veröffentlicht in:IEEE Transactions on robotics and automation 17, 5 (2001).
1. Verfasser: Stokes, D.
Format: Artikel
Sprache:English
Schlagworte:
AlGaAs.
GaAs.
Backpropagation.
Feedback.
Identification.
Indirect adaptive control.
Metal-semiconductor-metal structure.
Model-based control.
Neural networks.
Nonlinear system.
Reactive ion etching.
Real-time system.