Method and apparatus for attenuating error in dynamic and steady-state processes for prediction, control, and optimization

A computer-accessible memory medium for predicting an output value from a received input value, the memory medium comprising computer instructions executable by a processor to perform:

• modeling a set of static data received from a plant or process in a predictive static model over a first range, the static model having a static gain K and modeling static operation of the plant or process;
• modeling a set of dynamic data received from the plant or process in a predictive dynamic model over a second range smaller than the first range, the dynamic model having a dynamic gain k and modeling dynamic operation of the plant or process over the second range, and the dynamic model being independent of operation of the static model;
• adjusting the dynamic gain k of the dynamic model as a predetermined function of the static gain K of the static model to vary model parameters of the dynamic model;
• predicting the dynamic operation of the plant or process from an initial steady-state input value at a first time to a predicted steady-state input value at a second time to determine a predicted dynamic operation;
• comparing the predicted dynamic operation to a desired steady-state value of the plant or process at a final desired output value and generating an error as the difference therebetween;
• attenuating the error as a function of time between the first time and the second time;
• determining a change in the input value for input to said predicting the dynamic operation which is operable to vary the input value thereto;
• and
• varying the change in the input value in accordance with the determined change to minimize the attenuated error.

A system for predicting an output value from a received input value, comprising:

• a processor;
• a predictive static model implemented by the processor, wherein the predictive static models has a static gain K and models static operation of the plant or process, and wherein the predictive static model comprises a set of static data over a first range received from a plant or process;
• a dynamic model coupled to the predictive static model and implemented by the processor, wherein the dynamic model has a dynamic gain k and models dynamic operation of the plant or process, and wherein the dynamic model comprises a set of dynamic data over a second range smaller than the first range received from the plant or process;
• wherein the dynamic model is operable to:
• adjust the dynamic gain k as a predetermined function of the static gain K of the static model to vary model parameters of the dynamic model;
• predict the dynamic operation of the plant or process from an initial steady-state input value at a first time to a predicted steady-state input value at a second time to determine a predicted dynamic operation;
• compare the predicted dynamic operation to a desired steady-state value of the plant or process at a final desired output value and generate an error as the difference therebetween;
• attenuate the error as a function of time between the first time and the second time;
• determine a change in the input value for input to the dynamic model which is operable to vary the input value thereto;
• and
• vary the change in the input value in accordance with the determined change to minimize the attenuated error.

A system, comprising:

• means for modeling a set of static data received from a plant or process in a predictive static model over a first range, the static model having a static gain K and modeling static operation of the plant or process;
• means for modeling a set of dynamic data received from the plant or process in a predictive dynamic model over a second range smaller than the first range, the dynamic model having a dynamic gain k and modeling dynamic operation of the plant or process over the second range, and the dynamic model being independent of operation of the static model;
• means for adjusting the dynamic gain k of the dynamic model as a predetermined function of the static gain K of the static model to vary model parameters of the dynamic model;
• means for predicting the dynamic operation of the plant or process from an initial steady-state input value at a first time to a predicted steady-state input value at a second time to determine a predicted dynamic operation;
• means for comparing the predicted dynamic operation to a desired steady-state value of the plant or process at a final desired output value and generating an error as the difference therebetween;
• means for attenuating the error as a function of time between the first time and the second time;
• means for determining a change in the input value for input to said predicting the dynamic operation which is operable to vary the input value thereto;
• and
• means for varying the change in the input value in accordance with the determined change to minimize the attenuated error.