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Edward Balaban and Juan J. Alonso Win 2013 PHM Society Conference Best Paper Award
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Edward Balaban and Juan J. Alonso Win 2013 PHM Society Conference Best Paper Award

A paper by Edward Balaban and Juan J. Alonso (Stanford University, Department of Aeronautics and Astronautics) titled “A Modeling Framework for Prognostic Decision Making and its Application to UAV Mission Planning” was chosen as the best paper in the Applied category at the Annual Conference of the Prognostics and Health Management Society 2013. The conference was held in New Orleans, LA, October 14-17, 2013.

BACKGROUND: One of the goals of the System-wide Safety and Assurance Technologies (SSAT) project is to develop robust methods for implementing Prognostic Decision Making (PDM) in aeronautical applications, i.e., to utilize information on anticipated changes in vehicle health for selecting future actions. A key challenge in PDM is finding a sufficiently expressive yet compact mathematical representation of the system for use with decision optimization algorithms. The paper describes a general modeling approach for a class of PDM problems with non-linear system degradation processes and uncertainties in state estimation, action effects, and future operating conditions. The approach is based on continuous Partially Observable Markov Decision Processes (POMDPs) used in conjunction with 'black box' system simulations. The proposed modeling framework can be cast into simpler representations, depending on which sources of uncertainty are included. The overall approach is illustrated with a mission planning case study for an Unmanned Aerial Vehicle (UAV).

NASA PROGRAM FUNDING: Safety and Assurance Technologies (SSAT) project, Aviation Safety Program, Aeronautics Research Mission Directorate

COLLABORATORS: Abhinav Saxena (SGT) and Christopher Teubert (SGT)

Contact: Edward Balaban

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