Autonomous vehicle health monitoring (VHM) has been identified as a high priority technology for future space exploration in NASA's 2012 technology roadmap. Traditional VHM approaches are often designed for a specific application and are unable to detect and isolate a wide variety of faults. Proposed methods are often too computationally complex for NASA's manned flight software verification and validation (V&V) process. An innovative VHM algorithm is presented that addresses these weaknesses by integrating the constraint suspension technique with parity space and hypothesis testing. The approach relies on on-board sensor measurements, knowledge of control commands, and a modular mathematical system model to provide a VHM solution. Improvement over original constraint suspension is demonstrated using conceptual and numerical examples. Feasibility of the VHM method on a spacecraft is explored using a numerical simulation of a generic vehicle.


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    Title :

    Vehicle health monitoring using stochastic constraint suspension.
    VHM using stochastic constraint suspension



    Publication date :

    2012


    Size :

    92 pages


    Remarks:

    Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2012.
    Pages 91 and 92 blank. Cataloged from PDF version of thesis.
    Includes bibliographical references (p. 79-81).


    Type of media :

    Theses


    Type of material :

    Electronic Resource


    Language :

    English




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