2026-09-19T06:48:34Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/761082022-01-13T07:54:11Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Jeffrey A. Hoffman and Russell Sargent.
Rossi, Christopher, S.M. Massachusetts Institute of Technology
Massachusetts Institute of Technology. Dept. of Aeronautics and Astronautics.
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
2013-01-07T21:21:26Z
2013-01-07T21:21:26Z
2012
2012
http://hdl.handle.net/1721.1/76108
820469733
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).
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.
by Christopher Rossi.
S.M.
92 p.
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by
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http://dspace.mit.edu/handle/1721.1/7582
Aeronautics and Astronautics.
Vehicle health monitoring using stochastic constraint suspension
VHM using stochastic constraint suspension
Thesis
application/pdf
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Publication
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<Abstract>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.</Abstract>
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