Optimally Robust Redundancy Relations for Failure Detection in Uncertain Systems

Abstract

All failure detection methods are based, either explicitly or implicitly, on the use of redundancy, i.e. on (possibly dynamic) relations among the measured variables. The robustness of the failure detection process consequently depends to a great degree on the reliability of the redundancy relations, which in turn is affected by the inevitable presence of model uncertainties. In this paper, we address the problem of determining redundancy relations that are optimally robust, in a sense that includes several major issues of importance in practical failure detection, and that provides a significant amount of intuition concerning the geometry of robust failure detection. We also give a procedure, involving the construction of a single matrix and its singular value decomposition, for the determination of a complete sequence of redundancy relations, ordered in terms of their level of robustness. This procedure also provides the basis for comparing levels of robustness in redundancy provided by different sets of sensors.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1985
Accession Number
ADA459971

Entities

People

  • Alan S. Willsky
  • George C. Verghese
  • Xi-cheng Lou

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Computational Complexity
  • Computer Science
  • Covariance
  • Damage Detection
  • Decomposition
  • Detection
  • Detectors
  • Eigenvalues
  • Eigenvectors
  • Electrical Engineering
  • Failure Mode And Effect Analysis
  • Kalman Filters
  • Models
  • Redundancy
  • Reliability

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computer Programming and Software Development.
  • Statistical inference.