METHOD AND APPARATUS FOR DYNAMIC AND STEADY-STATE MODELING OVER A DESIRED PATH BETWEEN TWO END POINTS

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 rigorouspredictive model that is trained over a wide range of data, whereas thedynamic model (22) is trained over a narrow range of data. The gain K of thestatic 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 variablesare scaled by the ratio of the gains K and k. The bi have a direct effect onthe gain of a dynamic model (22). This is facilitated by a coefficientmodification block (40). Thereafter, the difference between the new valueinput to the static model (20) and the prior steady-state value is utilized asan input to the dynamic model (22). The predicted dynamic output is thensummed with the previous steady-state value to provide a predicted value Y.Additionally, the path that is traversed between steady-state value changes.