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This study introduces a robust sensor fault estimation method for nonlinear interconnected systems. The approach ensures rapid error convergence and simplifies gain matrix calculation for improved fault detection.

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Area of Science:

  • Control Systems Engineering
  • Fault Diagnosis and Fault Tolerance

Background:

  • Nonlinear interconnected systems are susceptible to sensor faults, compromising system performance and safety.
  • Accurate sensor fault estimation is crucial for maintaining the reliability of complex systems.

Purpose of the Study:

  • To develop a robust and efficient sensor fault estimation method for nonlinear interconnected systems.
  • To address the challenges posed by external disturbances in fault estimation.

Main Methods:

  • Proposed a fault estimation method based on system state reconstruction theory.
  • Constructed a generalized nonlinear interconnected system by augmenting system states and fault vectors.
  • Developed an augmented observer using equivalent transformation for robust fault estimation.

Main Results:

  • The proposed method demonstrated robustness against external disturbances.
  • Achieved rapid convergence of estimation errors (approaching 0 within 10 seconds).
  • The gain matrix calculation for the augmented observer was found to be convenient.

Conclusions:

  • The developed sensor fault estimation method is effective and reliable for nonlinear interconnected systems.
  • The method offers advantages in robustness, convergence speed, and computational convenience.
  • Simulation results validate the proposed approach, providing a reference for similar systems.