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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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Indirect-Neural-Approximation-Based Fault-Tolerant Integrated Attitude and Position Control of Spacecraft Proximity

Fawaz W Alsaade1, Qijia Yao2, Mohammed S Al-Zahrani3

  • 1Department of Computer Science, College of Computer Sciences and Information Technology, King Faisal University, Al-Ahsa 31982, Saudi Arabia.

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Summary
This summary is machine-generated.

This study introduces a neural adaptive fault-tolerant control scheme for spacecraft proximity operations, ensuring stable attitude and position control despite unknown parameters and actuator faults.

Keywords:
Lyapunov analysisfault-tolerant controlindirect neural approximationintegrated attitude and position controlneural adaptive controlspacecraft proximity operations

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Area of Science:

  • Aerospace Engineering
  • Control Systems
  • Artificial Intelligence

Background:

  • Spacecraft proximity operations require precise integrated attitude and position control.
  • Unknown parameters, external disturbances, and actuator faults pose significant challenges to control system reliability.

Purpose of the Study:

  • To propose a neural adaptive fault-tolerant control (NAFTC) scheme for robust integrated attitude and position control of spacecraft during proximity operations.
  • To address uncertainties, disturbances, and actuator faults without requiring prior model information.

Main Methods:

  • Developed a controller comprising relative attitude and relative position control laws.
  • Employed neural networks (NNs) for indirect approximation of unknown parameter bounds.
  • Utilized Lyapunov stability analysis to verify system boundedness and convergence.

Main Results:

  • The NAFTC scheme effectively handles unknown parameters, disturbances, and actuator faults.
  • The controller requires minimal adaptive parameters, reducing computational load.
  • Simulations demonstrated that relative attitude, angular velocity, position, and velocity converge to stable states.

Conclusions:

  • The proposed neural adaptive fault-tolerant control scheme offers a robust and efficient solution for spacecraft proximity operations.
  • The controller's model-free nature and reduced computational burden make it practical for real-world applications.
  • Validated effectiveness and superior performance through simulation, ensuring system stability and safety.