An integrated methodology for the dynamic performance and reliability evaluation of fault-tolerant systems

Alejandro Dominguez-Garcia, John G. Kassakian, Joel E. Schindall, Jeffrey J. Zinchuk

Research output: Contribution to journalArticle

Abstract

We propose an integrated methodology for the reliability and dynamic performance analysis of fault-tolerant systems. This methodology uses a behavioral model of the system dynamics, similar to the ones used by control engineers to design the control system, but also incorporates artifacts to model the failure behavior of each component. These artifacts include component failure modes (and associated failure rates) and how those failure modes affect the dynamic behavior of the component. The methodology bases the system evaluation on the analysis of the dynamics of the different configurations the system can reach after component failures occur. For each of the possible system configurations, a performance evaluation of its dynamic behavior is carried out to check whether its properties, e.g., accuracy, overshoot, or settling time, which are called performance metrics, meet system requirements. Markov chains are used to model the stochastic process associated with the different configurations that a system can adopt when failures occur. This methodology not only enables an integrated framework for evaluating dynamic performance and reliability of fault-tolerant systems, but also enables a method for guiding the system design process, and further optimization. To illustrate the methodology, we present a case-study of a lateral-directional flight control system for a fighter aircraft.

Original languageEnglish (US)
Pages (from-to)1628-1649
Number of pages22
JournalReliability Engineering and System Safety
Volume93
Issue number11
DOIs
StatePublished - Nov 1 2008

Keywords

  • Behavior
  • Behavioral model
  • Dynamic probabilistic risk assessment
  • Fault tolerance
  • Markov reliability modeling
  • Performance
  • Reliability

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Industrial and Manufacturing Engineering
  • Applied Mathematics

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