Marek Kowal and Józef Korbicz. Fault Detection under Fuzzy Model Uncertainty. International Journal of Automation and Computing, vol. 4, no. 2, pp. 117-124, 2007. DOI: 10.1007/s11633-007-0117-1
Citation: Marek Kowal and Józef Korbicz. Fault Detection under Fuzzy Model Uncertainty. International Journal of Automation and Computing, vol. 4, no. 2, pp. 117-124, 2007. DOI: 10.1007/s11633-007-0117-1

Fault Detection under Fuzzy Model Uncertainty

  • The paper tackles the problem of robust fault detection using Takagi-Sugeno fuzzy models. A model-based strategy is employed to generate residuals in order to make a decision about the state of the process. Unfortunately, such a method is corrupted by model uncertainty due to the fact that in real applications there exists a model-reality mismatch. In order to ensure reliable fault detection the adaptive threshold technique is used to deal with the mentioned problem. The paper focuses also on fuzzy model design procedure. The bounded-error approach is applied to generating the rules for the model using available measurements. The proposed approach is applied to fault detection in the DC laboratory engine.
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