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<p>Reliable motion tracking in avionic systems is essential for flight safety and predictive maintenance. Aircraft systems are affected by actuator faults, uncertainties, nonlinear dynamics, and measurement noise, which can degrade control and diagnostic performance. This paper proposes a fault detection strategy for an active landing gear system based on a Luenberger observer integrated into a six-degree-of-freedom aircraft dynamic model. The approach exploits global aircraft motion, including bounce, pitch, and roll dynamics, to ensure consistent state estimation and reliable fault detection. Simulation results show that the residuals remain close to zero under healthy operating conditions and increase significantly in the presence of actuator faults, enabling effective anomaly detection. A comparative study with the Kalman filter is also conducted. The results indicate that the Luenberger observer achieves estimation and fault detection performance comparable to that of the Kalman filter for the considered linear system under moderate uncertainty conditions. However, the proposed approach features lower computational complexity and does not require tuning of noise covariance matrices, making it particularly suitable for real-time embedded aerospace applications. These results highlight that a properly designed Luenberger observer, when consistently integrated with the physical dynamics of the system, can provide an effective and simple alternative to more complex stochastic estimation methods while maintaining comparable performance in aerospace applications.</p>

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A novel strategy for fault detection in aircraft active landing gear using observer based global motion analysis

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年6月15日

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  • Azeddine Ratni,
  • Djamel Benazzouz,
  • Mohammed Tsebia

摘要

Reliable motion tracking in avionic systems is essential for flight safety and predictive maintenance. Aircraft systems are affected by actuator faults, uncertainties, nonlinear dynamics, and measurement noise, which can degrade control and diagnostic performance. This paper proposes a fault detection strategy for an active landing gear system based on a Luenberger observer integrated into a six-degree-of-freedom aircraft dynamic model. The approach exploits global aircraft motion, including bounce, pitch, and roll dynamics, to ensure consistent state estimation and reliable fault detection. Simulation results show that the residuals remain close to zero under healthy operating conditions and increase significantly in the presence of actuator faults, enabling effective anomaly detection. A comparative study with the Kalman filter is also conducted. The results indicate that the Luenberger observer achieves estimation and fault detection performance comparable to that of the Kalman filter for the considered linear system under moderate uncertainty conditions. However, the proposed approach features lower computational complexity and does not require tuning of noise covariance matrices, making it particularly suitable for real-time embedded aerospace applications. These results highlight that a properly designed Luenberger observer, when consistently integrated with the physical dynamics of the system, can provide an effective and simple alternative to more complex stochastic estimation methods while maintaining comparable performance in aerospace applications.