Fault Detection and Isolation for Nonlinear Process Systems Using Asynchronous Measurements

This work addresses the problem of fault detection and isolation for nonlinear processes when some process variable measurements are available at regular sampling intervals and the remaining process variables are measured at an asynchronous rate. First, a fault detection and isolation (FDI) scheme that employs model-based techniques is proposed that allows for the isolation of faults. The proposed FDI scheme provides detection and isolation of any fault that enters into the differential equation of only synchronously measured states and grouping of faults that enter into the differential equation of any asynchronously measured state. For a fully coupled process system, fault detection occurs shortly after a fault takes place, and fault isolation, limited by the arrival of asynchronous measurements, occurs when asynchronous measurements become available. Fault-tolerant control methods with a supervisory control component are then employed to achieve stability in the presence of actuator failures using control system reconfiguration. Numerical simulations of a polyethylene reactor are performed to demonstrate the applicability and performance of the proposed fault detection and isolation and fault-tolerant control method in the presence of asynchronous measurements.