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Updated: Aug 15, 2025

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
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Fault Estimation Method for Nonlinear Time-Delay System Based on Intermediate Observer-Application on Quadrotor

Qingnan Huang1, Jingru Qi1, Xisheng Dai1

  • 1School of Automation, Guangxi University of Science and Technology, Liuzhou 545006, China.

Sensors (Basel, Switzerland)
|January 8, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a novel fault estimation algorithm for quadrotor unmanned aerial vehicles (QUAVs). The method effectively estimates simultaneous actuator and sensor faults, enhancing QUAV system reliability.

Keywords:
actuator faultfault estimationintermediate observerquadrotor UAVsensor fault

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Area of Science:

  • Control Engineering
  • Robotics
  • Fault Diagnosis

Background:

  • Quadrotor unmanned aerial vehicles (QUAVs) are susceptible to actuator and sensor faults.
  • System complexities include time delays, nonlinearities, and external disturbances during flight.
  • Accurate fault diagnosis is crucial for safe and reliable QUAV operation.

Purpose of the Study:

  • To develop a robust fault estimation algorithm for QUAVs.
  • To address both single actuator faults and simultaneous actuator and sensor faults.
  • To ensure the stability and boundedness of estimation errors.

Main Methods:

  • A fault estimation algorithm based on an intermediate observer is proposed.
  • For single actuator faults, an intermediate variable and observer are designed.
  • For simultaneous faults, system augmentation and two intermediate variables are utilized.
  • Lyapunov-Krasovskii functional is employed for stability analysis.

Main Results:

  • The proposed intermediate observer effectively estimates faults in the QUAV system.
  • The method successfully handles simultaneous actuator and sensor faults.
  • The estimation error system is proven to be uniformly eventually bounded.
  • Simulation results demonstrate the method's feasibility and effectiveness.

Conclusions:

  • The developed fault estimation algorithm enhances the safety and reliability of QUAVs.
  • The approach provides a robust solution for diagnosing complex fault scenarios.
  • This work contributes to the advancement of fault-tolerant control systems for aerial vehicles.