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Fault Isolation and Estimation in Networks of Linear Process Systems.

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Sensor Faults Isolation in Networked Control Systems: Application to Mobile Robot Platoons.

Wijaya Kurniawan1, Lorinc Marton2

  • 1Department of Electrical Engineering and Information Systems, University of Pannonia, 8200 Veszprem, Hungary.

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Summary

A new model for networked control systems effectively diagnoses sensor faults in robotics platoons. This approach enables weak sensor fault isolation by treating network disturbances as unknown inputs, ensuring system reliability.

Keywords:
Unknown Input Observermobile robot platoonsnetworked systemssensor faultsweak fault isolation

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Area of Science:

  • Control Systems Engineering
  • Robotics
  • Networked Systems

Background:

  • Sensor faults in networked control systems can propagate and impact multiple subsystems.
  • Existing methods may struggle with weak sensor faults and network-induced disturbances.

Purpose of the Study:

  • To propose a fault diagnosis-oriented model for linear networked control systems.
  • To design distributed Unknown Input Observers (UIO) for weak sensor fault isolation.
  • To apply the model to a robotics platoon with wireless leader-follower communication.

Main Methods:

  • Developed a fault diagnosis-oriented model for linear networked control systems.
  • Designed distributed Unknown Input Observers (UIO) to handle unknown inputs (network disturbances and fault propagation).
  • Implemented a case study using a wireless leader-follower robotics platoon.

Main Results:

  • The proposed model accurately simulated the behavior of a robotics platoon with sensor faults.
  • Distributed UIOs successfully isolated weak sensor faults by analyzing residual signals.
  • The approach demonstrated effectiveness in a realistic networked robotics scenario.

Conclusions:

  • The fault diagnosis-oriented model is effective for networked control systems, particularly in robotics platoons.
  • Distributed UIOs provide a viable method for weak sensor fault isolation in such systems.
  • The study validates the model's capability to manage network disturbances and fault propagation.