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Multi-level Pseudo-Random Signal Design and “ Model-on-Demand ” Estimation Applied to Nonlinear Identification of a RTP Wafer Reactor
| Content Provider | Semantic Scholar |
|---|---|
| Author | Braun, Martin W. Rivera, Daniel E. Stenman, Anders Foslien, Wendy Hrenya, Christine M. |
| Copyright Year | 1999 |
| Abstract | Guidelines are presented for specifying the design parameters of multi-level pseudo-random sequences in a manner useful for “plant-friendly” nonlinear system identification. These multi-level signals are introduced into a Rapid Thermal Processing wafer reactor simulation and compared against a well-designed pseudorandom binary sequence (PRBS). The resulting data serves as a database for a “Model on Demand” (MoD) predictor. MoD estimation is attractive because it requires less engineering effort to model a nonlinear plant, compared to global nonlinear models such as neural networks. The improved fit of multi-level signals over the PRBS signal, as well as the usefulness of the MoD estimator, is demonstrated on validation data. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://liu.diva-portal.org/smash/get/diva2:316029/FULLTEXT01.pdf |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Artificial neural network Bitstream Database Kerrison Predictor Mod (video gaming) Neural Network Simulation Nonlinear system identification Numerous Oral Wafer Procedural reasoning system Pseudo brand of pseudoephedrine Pseudorandom binary sequence Pseudorandomness Rapid thermal processing Reactor (software) Reactor Device Component Stochastic process Wafer (electronics) |
| Content Type | Text |
| Resource Type | Article |
