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| Detecting and diagnosing faults in dynamic stochastic distributions using a rational B-splines approximation to output PDFs |
| Hong WANG, Hong YUE |
| (Control Systems Centre Department of Electrical Engineering and Electronics, UMIST, Manchester M60 1QD, U. K. ; Institute of Automation, Chinese Academy of Sciences, Beijing 100080, China) |
| Abstract: |
| This paper presents a novel approach to detect and diagnose faults in the dynamic part of a class of stochastic systems . the Such a group of systems are subjected to a set of crisp inputs but the outputs considered are the measurable probability density functions (PDFs) of the system output, rather than the system output alone. A new approximation model is developed for the output probability density functions so that the dynamic part of the system is decoupled from the output probability density functions. A nonlinear adaptive observer is constructed to detect and diagnose the fault in the dynamic part of the system. Conver-gency analysis is performed for the error dynamics raised from the fault detection and diagnosis phase and an applicability study on the detection and diagnosis of the unexpected changes in the 2D grammage distributions in a paper forming process is included. |
| Key words: Fault detection and diagnosis Observer design Papermaking Stochastic systems |
