Model{based Da T A{drivenapproach to Robust Fault Diagnosis in Chemical Processes
نویسندگان
چکیده
This paper presents a robust model{based technique for the diagnosis of faults in a chemical process. The diagnosis system is based on the robust estimation of process outputs. A dynamic non{linear model of the process under investigation is obtained by a procedure exploiting T akagi{Sugeno (T-S) multiple{ model fuzzy iden ti cation. The combined iden ti cation and residual generation schemes have robustness properties with respect to modelling uncertainty, disturbance and measurement noise, providing good sensitivity properties for fault detection and fault isolation. The identi ed system consists of a fuzzy combination of T-S models to detect changing plant operating conditions. Residual analysis and geometrical tests are then suÆcient for F ault Detection and Isolation (FDI), respectively. The procedure here presented is applied to the problem of detecting and isolating faults in a benchmark simulation of a tank reactor chemical process.
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