发明名称 |
Method and apparatus for modeling dynamic and steady-state processes for prediction, control and optimization |
摘要 |
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 bl variables are scaled by the ratio of the gains K and k. The bi have a direct effect on the gain of a dynamic model (22). This is facilitated by a coefficient modification block (40). 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. Additionally, the path that is traversed between steady-state value changes.
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申请公布号 |
US2003078684(A1) |
申请公布日期 |
2003.04.24 |
申请号 |
US20020302923 |
申请日期 |
2002.11.22 |
申请人 |
MARTIN GREGORY D.;BOE EUGENE;PICHE STEPHEN;KEELER JAMES DAVID;TIMMER DOUGLAS;GERULES MARK;HAVENER JOHN P. |
发明人 |
MARTIN GREGORY D.;BOE EUGENE;PICHE STEPHEN;KEELER JAMES DAVID;TIMMER DOUGLAS;GERULES MARK;HAVENER JOHN P. |
分类号 |
G05B13/02;G05B13/04;G05B17/02;G05B21/02;(IPC1-7):G05B13/02 |
主分类号 |
G05B13/02 |
代理机构 |
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地址 |
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