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Reliable predictability of patterns in decentralized discrete-event systems.

Hongzhen Zhu1, Fuchun Liu1, Rui Zhao1

  • 1School of Computers, Guangdong University of Technology, Guangzhou, 510006, China.

ISA Transactions
|May 30, 2021
PubMed
Summary

This study introduces k-reliable pattern copredictability for decentralized systems, ensuring failure prediction even with site malfunctions. It presents algorithms and conditions for verifying this crucial predictability property.

Keywords:
CopredictabilityDecentralized fault predictionDiscrete-event systems (DESs)Pattern matchingReliable copredictability

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Area of Science:

  • Computer Science
  • Control Theory
  • Automation Systems

Background:

  • Predictability is vital for detecting unobservable failures in automation systems.
  • Failures can arise from single events or complex event strings (patterns).
  • Decentralized systems require distributed prediction capabilities.

Purpose of the Study:

  • Define and verify k-reliable pattern copredictability in decentralized Discrete Event Systems (DESs).
  • Ensure continued failure prognostication despite local site failures.
  • Develop efficient algorithms for predictability verification.

Main Methods:

  • Formal language definitions for k-reliable pattern copredictability.
  • Construction of nondeterministic automata: codiagnoser and coverifier.
  • Development of algorithms for verifying copredictability using these automata.

Main Results:

  • Formal definition of k-reliable pattern copredictability (1≤k≤r).
  • Necessary and sufficient conditions for copredictability established.
  • Polynomial complexity algorithms for coverifier construction and k-reliable copredictability verification.

Conclusions:

  • The proposed methods enable reliable pattern failure prediction in decentralized DESs.
  • The system maintains prognostication capability even when up to r-k sites malfunction.
  • Efficient verification algorithms ensure practical implementation for system reliability.