Real-time Performance Monitoring of MPC Based on Covariance Index Prediction

Abstract

Aiming at monitoring model predictive control performance real-timely by using process data,a covariance prediction error based performance monitoring method is proposed.On the basis of analyzing MPC optimal objective and control structure,a monitored variable set composed of prediction errors,manipulated variables and process output variables is developed.Then,a covariance based real-time performance assessment index is presented by adopting a moving window.For the problem that covariance index has no control limits,a time sequence model for real-time covariance index is presented.The predictive residual of covariance index is monitored to detect MPC performance deterioration.The source of performance deterioration can be located by using a performance diagnosis method based on data set similarity.Simulations on the WoodBerry binary distillation column demonstrate the effectiveness of the foregoing scheme.