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Presented By:
Anthony David Rosello
B.S., Engineering Science, United States Air Force Academy

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Abstract
A general two tier framework for Vehicle Health Monitoring of Guidance Navigation and Control (GN&C) system actuators, effectors, and propulsion devices is presented. In this context, a top level monitor that estimates jet thrust is designed for the Space Shuttle Reaction Control System (RCS) during the reentry phase of flight. Issues of importance for the use of estimation technologies in Vehicle Health Monitoring are investigated and quantified for the Shuttle RCS demonstration application. These issues include rate of convergence, robustness to unmodeled dynamics, sensor quality, sensor data rates, and information recording objectives. Closed loop simulations indicate that a Kalman filter design is sensitive to modeling error and robust estimators may reduce this sensitivity. Jet plume interaction with the aerodynamic flowfield is shown to be a significant effect adversely impacting the ability to accurately estimate thrust.


Introduction
A primary objective for the development of future aerospace vehicles is the significant reduction of life cycle costs. To achieve this objective, more vehicle autonomy will be required with less emphasis on ground operations and maintenance. Vehicle Health Management is a key technology that will help aerospace systems meet these higher expectations, particularly in reduction of operations cost. Vehicle Health Management systems, which include Vehicle Health Monitoring algorithms, will allow the autonomous observation of vehicle subsystems while in their normal operating environment. Vehicle Health Management systems include all components needed to characterize system performance including: sensors, data pathways, processors, and monitoring algorithms. Figure (1-0-1) illustrates the relationship between the management and monitoring systems. For the remainder of the text, VHM will refer to Vehicle Health Monitoring. The information provided by a VHM system can be used to identify off nominal performance, and possibly reconfigure to correct for degraded or failed performance. Off-line, the recorded VHM data may subsequently be used to warn of impending failure, better schedule and perform preventive maintenance, and detect problems that would otherwise remain unnoticed, until a later flight.


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http://dspace.mit.edu/bitstream/handle/1...sequence=1