Method and apparatus for minimizing error in dynamic and steady-state processes for prediction, control, and optimization
US9329582B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 10, 2012 |
| Grant date | May 3, 2016 |
| Priority date | — |
| Expiry date | Jan 22, 2035 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG09B23/02
- WIPO fieldControl
- WIPO sectorInstruments
Abstract
A method for providing independent static and dynamic models in a prediction, control and optimization environment utilizes an independent static model (20) and an independent dynamic model (22). The static model (20) is a rigorous predictive model that is trained over a wide range of data, whereas the dynamic model (22) is trained over a narrow range of data. The gain K of the static model (20) is utilized to scale the gain k of the dynamic model (22). The forced dynamic portion of the model (22) referred to as the bi variables are scaled by the ratio of the gains K and k. Thereafter, the difference between the new value input to the static model (20) and the prior steady-state value is utilized as an input to the dynamic model (22). The predicted dynamic output is then summed with the previous steady-state value to provide a predicted value Y.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.