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Abstract

A technique to provide dynamic modeling, parameter estimation and optimization for processes having operating targets. The technique has an optimization cycle and a simulation cycle. The simulation cycle runs at a rate that is equal to or faster than the run rate of the optimization cycle. Both cycles obtain data from the field about the process. The optimization cycle provides a simulation execution of a dynamic process model and the results of that simulation are used to match the model response to the actual plant response. This matching determines if a dynamic parameter estimation and data reconciliation is needed for the model parameters. Optimized operating targets are determined using either the estimated and reconciled parameters and data or if the same is not needed the collected process data. Mathematical and heuristic assessment tools are used to determine if the optimized operating targets should or should not be invoked.

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