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Fault diagnosis and fault-tolerant control for non-Gaussian nonlinear stochastic systems via entropy optimisation

Author

Listed:
  • Lina Yao
  • Lifan Li
  • Yacun Guan
  • Hao Wang

Abstract

In this paper, the fault diagnosis (FD) and fault tolerant control (FTC) problems are studied for non-linear stochastic systems with non-Gaussian disturbance and fault. Unlike classical FD algorithms, the minimum entropy FD is adopted to minimise the residual entropy and control the shape of the probability density function (PDF) of the residual signal. The observation error system can be proved to be locally and ultimately bounded in the mean square sense. Since entropy can be used to characteriSe the uncertainty of the tracking error for non-Gaussian stochastic systems, the FTC controller is obtained by minimising the performance function with regard to the entropy of the tracking error in this paper. The PDF of the output tracking error is approximated by the B-spline model. An illustrative example is utilised to demonstrate the effectiveness of the FD and FTC algorithm, and satisfactory results have been obtained.

Suggested Citation

  • Lina Yao & Lifan Li & Yacun Guan & Hao Wang, 2019. "Fault diagnosis and fault-tolerant control for non-Gaussian nonlinear stochastic systems via entropy optimisation," International Journal of Systems Science, Taylor & Francis Journals, vol. 50(13), pages 2552-2564, October.
    • Handle: RePEc:taf:tsysxx:v:50:y:2019:i:13:p:2552-2564
    DOI: 10.1080/00207721.2019.1671535
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