Predictive Alarm Generation for Chemical Processes with Unknown Disturbance

Abstract

AbstractA predictive warning generation scheme for chemical processes with unknown disturbances is proposed in this paper. The proposed methodology uses predicted states of a process system evaluated from the open loop process model and disturbance estimates. Alarms are issued for two conditions, during a time delay period and at the steady state. Disturbances are estimated using unknown input estimators. The moving horizon predictor combined with bias correction is used to predict the dynamic state of a process for a time‐delay period. To generate warnings for actuator limitations, steady state gain for disturbances along with input constraints are used to check for a feasible solution for using linear programming. A warning is generated to the operator when a feasible solution does not exist. The proposed methodology is demonstrated in a simulated model for a continuous stirred tank heater system (CSTH). Results show an early detection of an abnormal situation that provides the operator a lead time to react in the case of a disturbance affecting the system.