Ph.D. Defense: Peter Zane Schulte

Tue Jun 05 2018 01:00 PM to 03:00 PM
MK 317
“A State Machine Architecture for Aerospace Vehicle Fault Protection”

You're invited to hear

Ph.D. Defense

by

Peter Zane Schulte

(Advisor: Prof. David A. Spencer)

“A State Machine Architecture for Aerospace
Vehicle Fault Protection”

1p.m., Tuesday, June 5
MK 317

Abstract:
Because of their complexity and the unforgiving environment in which they operate, aerospace vehicles are vulnerable to mission-critical failures. In order to prevent these failures, aerospace vehicles often employ Fault Detection, Isolation, and Recovery (FDIR) systems to sense, identify the source of, and recover from faults. Typically, aerospace systems use a rule-based paradigm for FDIR where telemetry values are monitored against specific logical statements such as static upper and lower limits. The model-based paradigm allows more complex decision logic to be used for FDIR. State machines are a particular tool for model-based FDIR that have been explored by industry but not yet widely adopted. This study develops a generic and modular state machine FDIR architecture that is portable to flight software. The study will focus on FDIR for the Guidance, Navigation, & Control subsystem, but it will be presented in a manner that is applicable to all vehicle subsystems. The state machine formulation is applied for on-board model-based fault diagnosis. Two specific case studies are employed to demonstrate the architecture. The first is a terrestrial application of unmanned aerial vehicles for 3D scanning and mapping, which is validated through flight testing. The second is a space-based application of automated close approach and capture for a Mars sample return mission, which is validated through software-in-the-loop testing with flight-like software components.

Committee:

  • Prof. David A. Spencer, School of Aerospace Engineering (advisor), Georgia Tech
  • Prof. E. Glenn Lightsey, School of Aerospace Engineering, Georgia Tech
  • Prof. Mark Costello, School of Aerospace Engineering, Georgia Tech
  • Dr. Neil Smith, Visual Computing Center, King Abdullah University of Science and Technology
  • Mr. Paul Rosendall, Space Department, Johns Hopkins University Applied Physics Laboratory

Location

MK 317