Control performance monitoring of LP-MPC cascade systems

Traditional minimum variance control (MVC) based performance monitoring methods treats all controlled variables (CVs) the same (or with some preselected weights). However, due to the nature of soft CV constraint, CVs have priority in cascade systems of linear programming model predictive control (LP-MPC). It is desired to reduce violations of constraints for CVs at their upper or lower bounds and to keep CVs under control. In this paper, we introduce block lower triangular interactor matrix, based on which conditional MVC and corresponding performance benchmark is developed. We state that conditional MVC first consider CVs with multiple level priority and a subset of CVs in each level of priority. A simulation example is given to compare proposed method with traditional MVC methods.