Fault Detection and Isolation for the Bluebird Test Bed Aircraft

Abstract

A Fault Detection and isolation (FDI) algorithm design is presented using the Multiple Model algorithm technique for the Bluebird aircraft being developed at the Naval Postgraduate School. The requirement to maintain high performance in the dynamic system of the aircraft necessitates the use of FDI techniques to detect and isolate malfunctions in the sensors and actuators of the aircraft without using hardware redundancy. The solution presented makes use of analytical redundancy in a bank of Kalman filters. Statistical tests using Bayesian theory are applied on the filter's innovations to perform the task of detection and isolation. The algorithm was developed using MATLAB software from The Math Works, Inc. The work presented in this thesis is related only to the task of FDI. The remaining task of the monitoring system, reconfiguration and continued operation by the observed plant after a failure detection, will not be addressed.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1993
Accession Number
ADA277979

Entities

People

  • Mario J. Levesque

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Actuators
  • Aircrafts
  • Algorithms
  • Computational Science
  • Control Systems
  • Damage Detection
  • Data Science
  • Detection
  • Detectors
  • Estimators
  • Flight Control Systems
  • Information Science
  • Kalman Filters
  • Mathematical Filters
  • Operating Systems
  • Optimal Estimators
  • Statistical Algorithms

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Fault Tolerant Diagnosis of Black and White Balloon Isolation Tests Using ¥.
  • Robotics and Automation.

Technology Areas

  • AI & ML