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 pseudo-random 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.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings of the American Control Conference |
| Publisher | IEEE |
| Pages | 1573-1577 |
| Number of pages | 5 |
| Volume | 3 |
| State | Published - 1999 |
| Event | Proceedings of the 1999 American Control Conference (99ACC) - San Diego, CA, USA Duration: Jun 2 1999 → Jun 4 1999 |
Other
| Other | Proceedings of the 1999 American Control Conference (99ACC) |
|---|---|
| City | San Diego, CA, USA |
| Period | 6/2/99 → 6/4/99 |
ASJC Scopus subject areas
- Control and Systems Engineering