Steady‐state target calculation for constrained predictive control systems based on goal programming

A new method of steady‐state target calculation for constrained model predictive control (MPC) using goal programming has been developed to solve the problem that the result is not satisfactory when the optimization problem is infeasible or the feasible region is away from the desired working point owing to system dynamics. In this model, soft constraints adjustment and target relaxation have been adopted simultaneously to coordinate with the result. The goal priority factors are introduced to describe the priority of constraints and targets; thereby, the steady‐state target calculation is transformed into a goal‐programming problem with a standard linear programming form and is solved with some calculation in real time. Simulation is processed with the example of the Shell heavy oil fractionators' benchmark problem, and the result shows the validity of the proposed algorithm.