A steady-state target calculation method based on “point” model for integrating processes

Aiming to eliminate the influences of model uncertainty on the steady-state target calculation for integrating processes, this paper presented an optimization method based on “point” model and a method determining whether or not there is a feasible solution of steady-state target. The optimization method resolves the steady-state optimization problem of integrating processes under the framework of two-stage structure, which builds a simple “point” model for the steady-state prediction, and compensates the error between “point” model and real process in each sampling interval. Simulation results illustrate that the outputs of integrating variables can be restricted within the constraints, and the calculation errors between actual outputs and optimal set-points are small, which indicate that the steady-state prediction model can predict the future outputs of integrating variables accurately.