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Faulty measurement substitution and control reconfiguration by using a multivariate flow control loop.

Sergio R P Perillo1, Belle R Upadhyaya2, J Wesley Hines2

  • 1IPEN-CNEN/SP, Sao Paulo, Brazil.

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PubMed
Summary

This study demonstrates a fault-tolerant control strategy for industrial systems using empirical models. The research shows that accurate models enable systems to maintain operation despite sensor or actuator failures.

Keywords:
Control reconfigurationData-driven modelsFault-tolerant controlMeasurement substitutionSequential probability ratio test

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Area of Science:

  • Control Engineering
  • Industrial Automation
  • Systems Engineering

Background:

  • Instrumentation and control systems require robust monitoring for sensors, equipment, and actuators.
  • Developing effective fault detection and control reconfiguration strategies is crucial for system reliability.

Purpose of the Study:

  • To design and build a multivariate control loop test bed for research.
  • To develop and demonstrate a fault-tolerant control strategy using empirical models.
  • To investigate fault detection and control reconfiguration in a real-world system.

Main Methods:

  • A two-tank multivariate loop was designed and constructed as a research test bed.
  • A fault-tolerant control strategy was experimentally developed and demonstrated.
  • Data-based empirical models were used for fault detection and measurement substitution.
  • Control reconfiguration was tested in the presence of actuator failure.

Main Results:

  • The study successfully demonstrated a fault-tolerant control strategy in a single-tank configuration.
  • Empirical models proved effective in detecting faults and substituting faulty sensor data.
  • The multivariate control loop system showed resilience under degraded operating conditions.

Conclusions:

  • Data-based empirical models are feasible for real-time fault detection and system adaptation.
  • Accurate empirical models are essential for a control system to survive degraded conditions.
  • This research validates the robustness of multivariate control loops with fault-tolerant strategies.