FAILURE MODEL DETERMINATION IN A KNOWLEDGE-BASED CONTROL SYSTEM.

Chien Y. Huang, Robert Frank Stengel

Research output: Contribution to journalConference article

4 Scopus citations

Abstract

A technique for determining the most probable failure state of a restructurable control system is presented. The approach is to build a knowledge base that contains and makes use of inference mechanisms to deduce the most likely failures given the symptoms. The analysis is first carried out in a local sense, where only probabilistic information and causality are used to generate failure models, then in a global sense, where the models are grouped and heuristics are used to prune the number of candidate models. Procedures are illustrated using failure patterns of a generic database as well as a fault scenario for a hypothetical helicopter flight control system. It is concluded that the proposed methods are potentially capable of handling generic failures and are thus useful in truly restructurable control systems.

Original languageEnglish (US)
Pages (from-to)1643-1648
Number of pages6
JournalProceedings of the American Control Conference
StatePublished - Dec 1 1987

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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