Model predictive control for an IGCC gasifier

Model predictive control has been widely applied in process control because of its ability to handle multivariable systems along with loop interactions and constraints. In this paper, an MPC controller that based on a state-space form was proposed for the Shell gasifier and the parameter tuning methods were concluded for the controller design. Monte-Carlo experiments were utilized to test the robustness of the controller. The simulation results of the proposed controller were compared with the results of a probability-based robust optimal PI controller, and it just shows that MPC controller can achieve a better performance.