TY - GEN
T1 - Supervisory control of a pilot-scale cooling loop
AU - Villez, Kris
AU - Venkatasubramanian, Venkat
AU - Garcia, Humberto
AU - Rieger, Craig
PY - 2011
Y1 - 2011
N2 - We combine a previously developed strategy for Fault Detection and Identification (FDI) with a supervisory controller in closed loop. The combined method is applied to a model of a pilot-scale cooling loop of a nuclear plant, which includes Kalman filters and a model-based predictive controller as part of normal operation. The system has two valves available for flow control meaning that some redundancy is available. The FDI method is based on likelihood ratios for different fault scenarios which in turn are derived from the application of the Kalman filter. A previously introduced extension of the FDI method is used here to enable detection and identification of non-linear faults like stuck valve problems and proper accounting of the time of fault introduction. The supervisory control system is designed so to take different kinds of actions depending on the status of the fault diagnosis task and on the type of identified fault once diagnosis is complete. Some faults, like sensor bias and drift, are parametric in nature and can be adjusted without need for reconfiguration of the regulatory control system. Other faults, like a stuck valve problem, require reconfiguration of the regulatory control system. The whole strategy is demonstrated for several scenarios.
AB - We combine a previously developed strategy for Fault Detection and Identification (FDI) with a supervisory controller in closed loop. The combined method is applied to a model of a pilot-scale cooling loop of a nuclear plant, which includes Kalman filters and a model-based predictive controller as part of normal operation. The system has two valves available for flow control meaning that some redundancy is available. The FDI method is based on likelihood ratios for different fault scenarios which in turn are derived from the application of the Kalman filter. A previously introduced extension of the FDI method is used here to enable detection and identification of non-linear faults like stuck valve problems and proper accounting of the time of fault introduction. The supervisory control system is designed so to take different kinds of actions depending on the status of the fault diagnosis task and on the type of identified fault once diagnosis is complete. Some faults, like sensor bias and drift, are parametric in nature and can be adjusted without need for reconfiguration of the regulatory control system. Other faults, like a stuck valve problem, require reconfiguration of the regulatory control system. The whole strategy is demonstrated for several scenarios.
KW - Fault Detection and Identification
KW - Kalman filter
KW - Model Predictive Control (MPC)
KW - Supervisory control
KW - model-based diagnosis
UR - http://www.scopus.com/inward/record.url?scp=80053396237&partnerID=8YFLogxK
U2 - 10.1109/ISRCS.2011.6016092
DO - 10.1109/ISRCS.2011.6016092
M3 - Conference contribution
AN - SCOPUS:80053396237
SN - 9781424492930
T3 - Proceedings - ISRCS 2011: 4th International Symposium on Resilient Control Systems
SP - 75
EP - 80
BT - Proceedings - ISRCS 2011
T2 - 4th International Symposium on Resilient Control Systems, ISRCS 2011
Y2 - 9 August 2011 through 11 August 2011
ER -