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.
Vehicle health monitoring using stochastic constraint suspension.
VHM using stochastic constraint suspension
2012
92 pages
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).
Theses
Electronic Resource
English
Vehicle Health Monitoring Using Stochastic Constraint Suspension
British Library Conference Proceedings | 2012
|Optimal linear suspension with integral constraint
Automotive engineering | 1988
|VEHICLE HAVING THREE OR MORE TILTING WHEELS WITH REACTIVE CONSTRAINT SUSPENSION
European Patent Office | 2020
|