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Predictive Alarm Generation for Chemical Processes with Unknown Disturbance
Author(s) -
Khan Mohammad Aminul Islam,
Imtiaz Syed Ahmad,
Khan Faisal
Publication year - 2019
Publication title -
the canadian journal of chemical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.404
H-Index - 67
eISSN - 1939-019X
pISSN - 0008-4034
DOI - 10.1002/cjce.23426
Subject(s) - control theory (sociology) , disturbance (geology) , model predictive control , estimator , process (computing) , alarm , operator (biology) , computer science , steady state (chemistry) , state (computer science) , false alarm , state estimator , engineering , mathematics , algorithm , control (management) , artificial intelligence , statistics , paleontology , biochemistry , chemistry , repressor , transcription factor , gene , biology , aerospace engineering , operating system
A 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.