Air data system fault modeling and detection

Paul Freeman, Peter Seiler, Gary J. Balas

Research output: Contribution to journalArticlepeer-review

35 Scopus citations

Abstract

Aircraft pitot-static probes are essential to airspeed and altitude measurements and safe flight. Measurement integrity is typically achieved via sensor hardware redundancy and a voting system. Hardware redundancy imposes a cost and payload penalty. This paper investigates an analytical alternative to hardware redundancy requiring a mathematical model of faulted and unfaulted pitot-static probes. The most common probe faults-debris, ice, or water blockages-are modeled using physical air data relationships and experimental wind tunnel data. These models are used with a linear model of the NASA GTM aircraft at one flight condition to design robust fault detection filters. Two linear H ∞ filters are designed to detect faults, reject disturbances, and provide robustness to model errors. Performance is evaluated using experimentally derived fault models with nonlinear aircraft simulations that incorporate actuator uncertainty.

Original languageEnglish (US)
Pages (from-to)1290-1301
Number of pages12
JournalControl Engineering Practice
Volume21
Issue number10
DOIs
StatePublished - Oct 2013

Bibliographical note

Funding Information:
Thanks to Goodrich Sensors and Integrated Systems for access to their experimental facilities and financial resources. Thanks also to Bill Kunik, Brian Mathies, Tim Golly, and others who assisted in this effort. This material is based upon work supported by the National Science Foundation under Grant no. 0931931 entitled CPS: Embedded Fault Detection for Low-Cost, Safety-Critical Systems. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the National Science Foundation.

Copyright:
Copyright 2013 Elsevier B.V., All rights reserved.

Keywords

  • Aerospace
  • Air data
  • Fault detection
  • Robust estimation
  • Sensor faults

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