Data processing: generic control systems or specific application – Generic control system – apparatus or process – Optimization or adaptive control
Reexamination Certificate
2006-02-21
2009-10-27
Tran, Khoi (Department: 3664)
Data processing: generic control systems or specific application
Generic control system, apparatus or process
Optimization or adaptive control
C700S029000, C700S037000, C700S039000, C700S065000, C700S072000, C703S002000, C703S016000, C703S018000, C703S023000, C901S003000, C901S042000, C901S015000, C901S016000, C901S021000, C318S560000, C318S568100, C318S632000, C414S005000, C414S006000, C414S331030, C414S331040
Reexamination Certificate
active
07610108
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 bivariables are scaled by the ratio of the gains K and k. The bihave 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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Boe Eugene
Martin Gregory D.
Piche Stephen
Fletcher Yoder Law
Marc McDieunel
Rockwell Automation Technologies Inc.
Tran Khoi
Walbrun William R.
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