×

Non-linear adaptive fault detection filter. (English) Zbl 0741.93033

Summary: A novel nonlinear adaptive fault detection filter (NAFDF) is proposed. It can be used to detect online and isolate the faults of a class of nonlinear systems arising from accidental jumps of the process parameters. The extended Kalman filter and weighted sum-squared residual method are first combined to detect the faults rapidly. A nonlinear filter is then proposed and used for joint state and parameter estimation of the system, resulting in a series of parameters. Based on them, Bayes’ decision algorithm is modified and used to isolate and classify the faults. An alternate initialization method is also presented, which makes it possible to detect and isolate the faults repeatedly. Finally, the effectiveness of the NAFDF is demonstrated by a simulation study.

MSC:

93C10 Nonlinear systems in control theory
PDFBibTeX XMLCite
Full Text: DOI

References:

[1] DONGHUA ZHOU , YUGENG , XI and ZHONGJUN ZHANG , 1989 , A fault detection method and application for nonlinear systems ,Proc. 4th Chinese Symposium on Control Techniques of Space and Movement Body, pp. 366 – 374 ; 1990,Inf. Control,19, 22 .
[2] FRANK , P. M. , 1987 , Fault diagnosis in dynamic systems via state estimation–a survey ,Proc. 1st European Workshop on Fault Diagnostics, Reliability and Related Knowledge-based Approach, 1 , pp. 35 – 98 . · doi:10.1007/978-94-009-3929-5_2
[3] ISERMANN R., Automatica 20 pp 387– (1984) · Zbl 0539.90037 · doi:10.1016/0005-1098(84)90098-0
[4] ZHOU WEI-WU, I.E.E.E. Trans, autom. Control 34 pp 312– (1989) · Zbl 0666.93120 · doi:10.1109/9.16421
[5] WILLSKY A. S., Automatica 12 pp 601– (1976) · Zbl 0345.93067 · doi:10.1016/0005-1098(76)90041-8
[6] WILLSKY , A. S. , DEYST , JR. , J. J. , and CRAWFORD , B. S. , 1974 , Adaptive filtering and self-text methods for failure detection and compensation ,Proc. 1974 JACC, pp. 637 – 645 .
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.