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Robust Sensor Fault Reconstruction via a Bank of Second-Order Sliding Mode Observers for Aircraft Engines

Author

Listed:
  • Zijian Qiang

    (Jiangsu Province Key Laboratory of Aerospace Power System, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

  • Jinquan Huang

    (Jiangsu Province Key Laboratory of Aerospace Power System, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

  • Feng Lu

    (Jiangsu Province Key Laboratory of Aerospace Power System, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

  • Xiaodong Chang

    (Jiangsu Province Key Laboratory of Aerospace Power System, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

Abstract

This paper deals with sensor faults of aircraft engines under uncertainties using a bank of second-order sliding mode observers (SMOs). In view of the effect of inevitable uncertainties on the fault reconstruction, a method combining H ∞ concepts and linear matrix inequalities (LMIs) is proposed, in which a scaling matrix is designed to minimize the gain of the transfer function matrix from uncertainty to reconstruction. However, robust design generally requires that engine outputs outnumber faults. In the case where the above-mentioned requirement is not satisfied, a bank of sliding mode observers is proposed to ensure the degrees of freedom available in robust design. In specific, each observer corresponds to a certain sensor with the hypothesis that the corresponding sensor will not have faults, to create one degree of design freedom for each observer. After fault occurrence, a large estimation error is expected in the observers with wrong hypothesis, and then a logic module is designed to detect sensor faults and obtain the optimal robust sensor fault reconstruction at the same time. The proposed approach is applied to a nonlinear engine component-level-model (CLM) simulation platform, and a numerical study is performed to validate the effectiveness.

Suggested Citation

  • Zijian Qiang & Jinquan Huang & Feng Lu & Xiaodong Chang, 2019. "Robust Sensor Fault Reconstruction via a Bank of Second-Order Sliding Mode Observers for Aircraft Engines," Energies, MDPI, vol. 12(14), pages 1-20, July.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:14:p:2831-:d:250742
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    References listed on IDEAS

    as
    1. Feng Lu & Jinquan Huang & Yiqiu Lv, 2013. "Gas Path Health Monitoring for a Turbofan Engine Based on a Nonlinear Filtering Approach," Energies, MDPI, vol. 6(1), pages 1-22, January.
    2. Xiaodong Chang & Jinquan Huang & Feng Lu, 2017. "Health Parameter Estimation with Second-Order Sliding Mode Observer for a Turbofan Engine," Energies, MDPI, vol. 10(7), pages 1-19, July.
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