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Multi-faults detection and estimation for nonlinear stochastic system based on particle filter and hypothesis test

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  • Bo Ding
  • Huajing Fang

Abstract

This paper is concerned with the fault detection and estimation for nonlinear stochastic system with additive multi-faults. The states of system are estimated by the improved particle filter which composed of basic particle filter and preliminary fault estimation. Since the preliminary fault estimation contains noise, the faults are detected by the method of hypothesis testing, while the amplitude of each fault is estimated by the average of the sample of preliminary fault estimation. Meanwhile, the relationship of the sample size, the significance level of two types of error, the amplitude of fault and the variance of the error of preliminary fault estimation are also given. The effectiveness of the proposed method is verified by the simulation of three-vessel water tank system.

Suggested Citation

  • Bo Ding & Huajing Fang, 2016. "Multi-faults detection and estimation for nonlinear stochastic system based on particle filter and hypothesis test," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(16), pages 3812-3821, December.
    • Handle: RePEc:taf:tsysxx:v:47:y:2016:i:16:p:3812-3821
    DOI: 10.1080/00207721.2015.1126381
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    References listed on IDEAS

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    1. Editors, 2014. "International Journal of Systems Science," International Journal of Systems Science, Taylor & Francis Journals, vol. 45(12), pages 1-1, December.
    2. Xiongbo Wan & Huajing Fang, 2013. "Fault detection for discrete-time networked nonlinear systems with incomplete measurements," International Journal of Systems Science, Taylor & Francis Journals, vol. 44(11), pages 2068-2081.
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